Robert P Biuk-Aghai
email: robertb@umac.mo

Hari Venkatesan
email: hariv@umac.mo

TransWiki: Supporting Translation Teaching

Keywords: wiki, translation, collaborative learning

Web-based learning systems have become common in recent years and wikis, websites whose pages anyone can edit, have enabled online collaborative text production. When applied to education, wikis have the potential to facilitate collaborative learning. We have developed a customized wiki system which we have used at our university in teaching translation in collaborative student groups. We report on the design and implementation of our wiki system and an evaluation of its use.

Introduction

Computer Supported Collaborative Learning (CSCL) became a reality with advances in technology and notably the advent of the Internet. Computer Aided Instruction, the precursor to CSCL, brought about automation of data dissemination, test-taking, language drills etc. that radically changed the classroom. As technology improved around the mid-1990s, computers and the emerging internet began to be seen as potential tools for creating new learning environments [START_REF] Alavi | Computer-mediated collaborative learning: an empirical evaluation[END_REF], moving away from the mostly uni-directional lecture format of teaching. In 1995 Ward Cunningham created the first wiki [START_REF] Leuf | The Wiki Way: Quick Collaboration on the Web[END_REF], a web site whose pages could be read and modified by anyone with access to the internet. Wikis could act as repositories for storage and dissemination of information and the collaborative production of assignments, projects, essays etc. We describe one implementation of a wiki that aims to provide a collaborative learning environment for translation.

The following section provides an overview of related work on using wikis in education. Section 3 then introduces our wiki design and implementation, and Sect. 4 presents an evaluation of the use of our wiki system at our university. Finally, Sect. 5 makes conclusions.

In the field of education, the past few years have witnessed increased adoption of wikis [START_REF] Pusey | Heuristics for implementation of wiki technology in higher education learning[END_REF]. Generally they are being used in two principal ways: as knowledge repositories for instructors making lecture material and course information available [START_REF] Schwartz | Educational wikis: features and selection criteria[END_REF]; and for the collaborative production of content by students, such as assignments, projects, essays and other assessment material [START_REF] Bruns | Wikis in teaching and assessment: the m/cyclopedia project[END_REF][START_REF] Lund | Is there a space for the teacher in a wiki?[END_REF]. Examples of the diverse uses which wikis were put to include: collaborative construction of encyclopedia entries by upper secondary school students [START_REF] Lund | Is there a space for the teacher in a wiki?[END_REF] and university students [START_REF] Bruns | Wikis in teaching and assessment: the m/cyclopedia project[END_REF]; collaborative creation of course content [START_REF] Wang | Extending the wiki paradigm for use in the classroom[END_REF] or a shared artefact [START_REF] Hampel | Deployment of simple user-centered collaborative technologies in educational institutions -experiences and requirements[END_REF] by university students; project management in a project-oriented computer science course [START_REF] Xu | Project the wiki way: using wiki for computer science course project management[END_REF]; project-oriented product development in an online graduate course [START_REF] Icaza | Project oriented immersion learning: Method and results[END_REF]; essay writing in a university ESL course [START_REF] Wang | An empirical exploration of using Wiki in an English as a second language course[END_REF], and for both short and semester-long assignments in a graduate course [START_REF] Bower | Wiki pedagogy-a tale of two wikis[END_REF]; and for developing knowledge management processes [START_REF] Biasutti | Using wiki in teacher education: Impact on knowledge management processes and student satisfaction[END_REF]. Wikis have been found to be effective in supporting learning [START_REF] Šerbec | Assessment of wiki-supported collaborative learning in higher education[END_REF][START_REF] Tsai | Collaborative learning using wiki web sites for computer science undergraduate education: A case study[END_REF][START_REF] Tselios | Effectiveness of a framed wiki-based learning activity in the context of hci education[END_REF], although the success of wikis may depend on assessment and grades as a form of reward for user contributions [START_REF] Ebner | Utilizing wiki-systems in higher education classes: a chance for universal access? Univers[END_REF].

The wiki concept as developed by Cunningham is an open one, where anyone can access and modify any page. This is for example largely the way that the MediaWiki system (www.mediawiki.org) underlying the Wikipedia site works although there are facilities for protecting pages from editing. For educational purposes some degree of access control is usually necessary, e.g. to protect pages that should only be editable by instructors but not by students. Moreover, in order to allow identification of contributions and to prevent changes by outsiders, anonymous editing may need to be disabled and students may be required to login [START_REF] Raitman | Security in the online e-learning environment[END_REF]. It has also been observed that a single tool integrating all required functions for communication, project management and authoring is preferable to a set of separate tools [START_REF] Icaza | Project oriented immersion learning: Method and results[END_REF]. Basic wiki technology has thus been extended with several different functions specifically for use in education: protecting/locking pages, creating read-only snapshots of an entire wiki site, and others [START_REF] Wang | Extending the wiki paradigm for use in the classroom[END_REF][START_REF] Elrufaie | A wiki paradigm for use in it courses[END_REF].

TransWiki

Our translation wiki system, named TransWiki, is based on the open source MediaWiki system which is the wiki engine of Wikipedia and many other popular wiki sites. MediaWiki is designed for a very open editorial process in which by default every user has read and edit privileges to every page. This can, however, be restricted by locking pages, which in the case of Wikipedia is done whenever edit wars break out on hotly contested pages dealing with controversial topics.

Whereas this open design is suitable for wikis with egalitarian contributors, it is not very suitable for use in education where there are clearly distinct roles of instructor and student. Therefore we have tailored MediaWiki for the use in education through a collection of extension packages that can be added onto an existing MediaWiki installation. An extension essentially provides a plugin that extends the functionality of the MediaWiki system. We have made our extensions available as an open source package named UMEduWiki3 . The system structure of TransWiki is shown in Fig. 1. On the server side, the base MediaWiki system is extended by our UMEduWiki extension package, and each of these has its own database (lower portion of Fig. 1, server and database layers). On the client side a unified TransWiki user interface is presented, which consists of both MediaWiki and UMEduWiki portions, and communicates with each of these server components (upper portion of Fig. 1, client layer). The base MediaWiki system provides basic wiki functionality: reading and editing of wiki pages, asynchronous online discussion through so-called discussion pages which are attached to wiki article pages, searching, viewing the revision history for any page, as well as several less frequently used wiki editing functions that are normally used by wiki administrators such as locking pages, moving pages, blocking users, and more. TransWiki extends this basic functionality of MediaWiki through following additional functions:

-Group-based access control -Access log -Forum-style discussions -Embedded audio playback
We briefly describe each of these below.

Access Control

Many wikis adopt a "free for all" access model where (almost) every user can perform (almost) every operation. This is not well suited for use in education where instructors and students have distinct roles and need to perform different operations. For example, an instructor may wish to arrange students in separate groups and assign them to do group work. During the process of the group work, the instructor may want to ensure that no group can view the outputs of any other groups' work. However, after the completion of the assigned work the instructor may wish to lock all contributions to prevent further editing (to perform grading of the assignment), and may decide to simultaneously open read access to all groups' pages to each other to let them compare their own outcomes with those of their peers. This is the model we have adopted in our translation courses, and it requires a more fine-grained and sophisticated access control than MediaWiki provides.

Our access control component uses a group-based access control model. An instructor or other suitably privileged user can create groups, such as instructor and student groups, or multiple student groups for when a class is divided into several groups. Students are then assigned to these groups. Along with each group we also create a MediaWiki namespace, which allows related pages to be grouped together and be collectively controlled. Students can create pages that belong to their namespace, and instructors can then control access to these pages. Access can be either read or edit. When neither of these is defined then this corresponds to no access rights at all. Access is granted for all the pages of a specified group. For example, an instructor may initially allow groups 1 and 2 only read and edit access to their own pages, then after completing an assignment remove the edit access and at the same time assign read access to each other's pages to share each group's outcome with each other. This kind of access control model may be called medium-grained, lying between the coarse-grained access control of the standard MediaWiki system in which all users are divided into a few roles (user, administrator, sysop etc.) with access permissions having a sitewide scope, and fine-grained access control in other systems where the specific permissions for each user can be set differently on an object-by-object basis. In our experience, this medium-grained access control model combines simplicity with effectiveness and is "fine grained enough" for our purposes. Figure 2 shows the user interface of the privilege management part of our access control panel. The user can select one or more groups on the left (G11, G12, G13, Teacher) to whom to assign the access privilege, select the type of access (read and/or edit), and select to which groups' pages the access should be granted, shown on the right (G11, G12, G13, Teacher).

Access Log

Wiki engines such as MediaWiki usually record when a user edits a page, including the version, date and time of the edit, a user-provided summary, and some other information. However, MediaWiki does not record when a user views a wiki page. To assess the involvement of students in online activities instructors usually wish to know about both reading and editing of wiki pages by students. Therefore we have developed an access log extension as a MediaWiki special page. This special page, which is only visible to instructors, shows who read or edited a page, and when. It provides options to filter the list by user, action, and/or namespace, and limit the number of days to show. It also provides an option to purge old log entries. The Access Log is effective in showing instructors the participation of students in the wiki.

Discussion Forum

Wiki discussion pages in MediaWiki are simply unstructured wiki pages that can be edited by any user, just as regular wiki pages. This is simple but does not always result in a readable record of the discussion as it lacks threading and sorting of discussion statements. Our earliest attempt to remedy this situation was a customized discussion page in which the page was not editable in the usual way but users could only append new posts to the end of the page. We also automatically added a signature line after each post including user name and a timestamp. This was an improvement over the default discussion page as it provided a chronologically sorted record of discussion posts, but all posts were in a single consecutive sequence without any separate threads, making it difficult to keep track of a discussion on a specific topic. Subsequently we developed an entirely new discussion function, with its own separate database tables. This discussion function supports two types of discussion statements: posts and replies. A post effectively starts a new thread, whereas a reply is a statement made in reply to a given post. This limits our discussion forum to just two levels, unlike other discussion forums that allow deeply nested discussions. Our purpose in doing so was to keep the discussions simple while supporting distinct threads. Moreover, we designed the user interface of our discussion forum to closely resemble that of Facebook posts and comments (see Fig. 3). An "agree" link is provided on each post and reply statement, analogous to the "like" link in Facebook. Students are encouraged to click it to indicate agreement with the statement made. This has the effect that one can quickly gauge which proposed translations find widespread acceptance in the group and which not. Clicking on "agree" is also more subtle than directly expressing agreement or disagreement through written statements, which many of our students avoid in order not to offend their fellow students. A lack of "agree's" thus implies disagreement, but without explicitly stating so. As practically all our students are active Facebook users, having a Facebook-like appearance achieves instant familiarity with our discussion function. In online collaborative translation, discussions play an important role in helping move the collective translation work forward by discussing the suitable way to translate a given text. In teaching translation, instructors need ways to assess not only the outcome of the translation, i.e. the target text, but also the process which led up to this outcome, which is recorded in the online discussion. To facilitate assessment of discussions, we have extended the instructor's view of the discussion forum with two additional functions: a rating function and a tagging function. Ratings allow the instructor to indicate how significant a contribution the given discussion post has made and are on a 5-point Likert scale (-2, -1, 0, 1, 2). Tags indicate the type of contribution made, and can be one of the following nine options: Informative, Argumentative, Evaluative, Elicitative, Responsive, Confirmation, Directive, Off task, or Off task technical. Rating and tagging together thus capture both a quantitative as well as a qualitative assessment of each discussion statement.

Audio Player

Our translation teaching includes the teaching of simultaneous interpretation. To integrate the teaching of interpretation into the wiki, we upload mp3 audio files of spoken interpretation exercises to our wiki. A MediaWiki extension that provides a public-domain mp3 player is seamlessly embedded directly in a wiki page to play back these audio files.

Evaluation

We deployed the TransWiki system at our university in the year 2007 and have used it since in two of our undergraduate translation classes which teach Chinese-English translation. Classes were divided into groups of 4-5 students each. These were composed of students with maximum variety of backgrounds, i.e. local students vs. those from mainland China, students from Chinese medium high schools vs. those from English medium high schools, etc. The underlying assumption in this modus operandi is that collaboration among students in producing the translation will result in interaction, peer review and discussion that would help students better understand the subject. As Tudge observes "...Research based on this model has indicated that social interaction between peers who bring different perspectives to bear upon a problem is a highly effective means of inducing cognitive development" [START_REF] Tudge | Vygotsky, the zone of proximal development, and peer collaboration: Implications for classroom practice[END_REF]. Furthermore, the social constructivist perspective on learning that we embrace in the teaching of translation holds that it is "by communicating and negotiating with peers and more experienced (and thus more knowledgeable) others, we acquire a feel for correctness, appropriateness and accuracy, a feel that is grounded in our social experiences..." [START_REF] Király | A social constructivist approach to translator education: Empowerment from theory to practice[END_REF]. Thus discussion and collaborative construction of translations are core to the development of translation skills.

Students were given assignments of translating a source text (in either English or Chinese) into the target language (i.e. from English to Chinese, or from Chinese to English). The discussion among group members was to be conducted in the assignment's discussion page inside TransWiki, and at the end when group consensus on the translation had been reached, the resulting target text was to be placed in the assignment wiki page. About 1-2 weeks were allocated for each assignment and about 3-4 assignments were given per semester. After the submission and grading of each assignment, the translated texts from each group were opened for all groups to view and were discussed in class.

At the end of each semester we conducted a survey to assess student attitudes toward the use of TransWiki. These focused on two main areas: (1) collaborative learning and (2) the TransWiki system. Below are the ten survey statements used in the most recent (April 2012) survey.

1. Doing assignments in a group helped improve the quality of translation 2. Discussing assignments exposed me to different ways in which language is used across regions/countries 3. I was able to freely express opinions/disagreement during discussions 4. My group managed to arrive at consensus through discussion 5. I would prefer working on assignments individually 6. Using a web-based platform for discussions was convenient 7. Transwiki was easy to learn and access 8. The discussion page facilitated discussions 9. I would like a live-chat function for discussions 10. I would like a discussion page that reflects changes instantly and automatically Statements 1-5 concerned collaborative learning, statements 6-10 concerned the TransWiki system. A total of 27 students responded whose answers are summarized in Table 1. The results show a strong support for collaborative translation (statements 1 and 2, 81% and 65% support, respectively). Even when asked whether students preferred working individually rather than collaboratively (statement 5), only about one third of students expressed this preference, As before, students favour a more real-time discussion facility, with the larger portion of students expressing a preference for an automatically updating discussion page (81% support). Given this feedback we have in the meantime developed such an instantly updating discussion page using AJAX, similar to the Facebook discussion page, and are deploying it for use in the current semester.

Overall the surveys suggest that working with TransWiki has been generally productive and that the system was well received. Students had complaints regarding the system's speed, especially updating postings on the discussion page. However, use of the discussion page was also appreciated by students who identified lack of peer pressure to agree/conform, as in face-to-face discussions, as one of TransWiki's advantages. The issue of speed was less important where groups allowed discussions to spread out over the entire length of time allowed instead of trying to get together at an appointed time. Such groups generally used the notification function in the wiki which informs students by e-mail once a group member makes a posting. The discussion page is indeed the most important feature of TransWiki as it is at the core of providing a collaborative platform for learning. It also allows all group discussions to be recorded, thus aiding evaluation by the instructor and providing useful insights as to potential problems faced by students. This allows for more focused and individualized teaching.

Regarding disadvantages of the system, a certain portion of students found working with TransWiki cumbersome or difficult. Key areas of complaint included having to log in to the TransWiki page repeatedly, the overall time consumed by the exercise, and discomfort with using computers.

In sum, the use of TransWiki can aid both learning and evaluation. The modus operandi described in this paper also serves as a framework for implementation of constructivist learning environments using TransWiki. The key ad-vantage is the ability to monitor and evaluate the actual collaboration that takes place (if at all). On the other hand ready access to computers and the internet, and being comfortable with using computers over an extended period of time for collaborative assignments are preconditions for successful implementation.

Conclusions

We have presented TransWiki, a customized wiki system for use in translation teaching. Our design is based on the existing MediaWiki system, extended with custom code developed by us. In the translation community it is well established that collaborative translation produces better quality results than individual translation. The challenge, however, lies in actually bringing about collaboration among a group of translators. Our experience with our students confirms that TransWiki facilitates online collaboration and discussion on translation. Through TransWiki students feel free to express their opinions and to collaborate, which is particularly relevant for the Asian context where students often hold back their opinions in face-to-face settings but feel more free to express themselves online. TransWiki's features enable instructors to provide separate working areas for separate student groups, enabling focused group work. Moreover, having a digital record not only of the finished translations but also of the communication within each group that led to the translation allows instructors to review and assess both process and outcome of translation, and to identify how learning has occurred. Thus TransWiki is both an enabling platform for collaborative translation and a pedagogical tool for translation teaching.

The design and implementation of TransWiki are not limited to use in translation, however. Other online collaborative work that involves joint construction of content should equally benefit from the features provided by TransWiki.

Fig. 1 .

 1 Fig. 1. TransWiki system structure

Fig. 2 .

 2 Fig. 2. TransWiki privilege management

Fig. 3 .

 3 Fig. 3. TransWiki discussion

Table 1 .

 1 TransWiki evaluation results (percentages)whereas another third expressed the opposite preference and the remaining students were neutral on this issue. Asked about TransWiki, the majority of students supported it in terms of learning and use (statements 6-8, with 58%, 63% and 50.0% support, respectively). Statements 9-10 asked for feedback regarding the discussion function which had attracted student criticism in the past.

	Statement Strongly Agree Agree Neutral Disagree Strongly Disagree
	1	11.1	70.4	14.8	3.7	0.0
	2	19.2	46.2	26.9	7.7	0.0
	3	15.4	65.4	11.5	7.7	0.0
	4	12.0	56.0	28.0	4.0	0.0
	5	7.7	26.9	30.8	23.1	11.5
	6	23.1	34.6	7.7	19.2	15.4
	7	25.9	37.0	11.1	25.9	0.0
	8	7.7	42.3	26.9	19.2	3.8
	9	20.0	40.0	32.0	8.0	0.0
	10	50.0	30.8	19.2	0.0	0.0

http://umeduwiki.sourceforge.net/


Bo Liu

Baokang Zhao

Dingjie Zou

Chunqing Wu
email: chunqingwu@nudt.edu.cn

Wanrong Yu

Ilsun You
email: isyou@bible.ac.kr

A Real-time Privacy Amplification Scheme in Quantum Key Distribution

Keywords: QKD, privacy amplification, security

QKD (Quantum Key Distribution) technology, based on the laws of physics, can create an unconditionally secure key between communication parties. In recent years, researchers draw more and more attention to the QKD technology. Privac amplification is a very significant procedure in QKD system. In this paper, we propose the real-time privacy amplification (RTPA) scheme which converts the weak secret string W to a uniform key that is fully secret from Eve. We implement RTPA scheme based on CLIP (Cvqkd Ldpc experImental Platform) which is connected to the real quantum communication systems. Experimental results show that, our proposed RTPA scheme is very efficient when the bit error rate of quantum channel is lower than 0.06.

Introduction

Quantum Key Distribution (QKD) [START_REF] Bennett | Quantum Cryptography: Public Key Distribution and Coin Tossing[END_REF][START_REF] Ekert | Quantum cryptography based on Bell theorem[END_REF] is technology for solving the key distribution problem. QKD system, based on the laws of physics, rather than the computational complexity of the mathematical problems assumed by current cryptography methods, can create an unconditionally secure key between communication parties. These keys are generated over unsecured channels, where may exist an active computationally unbounded adversary Eve.

After the procedure of information reconciliation [START_REF] Brassard | Secret-key reconciliation by public discussion[END_REF], Alice and Bob have own almost uniform keys with comparative low BER (Bit Error Rate). But Eve may have partial knowledge about the keys by eavesdropping or other ways.

Therefore, in order to gain the absolutely security keys, we must ensure the keys are privacy amplified. Privacy amplification (PA) [START_REF] Bennett | Generalized privacy amplification[END_REF] is a technology, through a public channel, to improve the information confidentiality. Privacy amplification converts the weak secret string W to a uniform key that is fully secret from Eve.

Privacy amplification technology typically applies a random and public hash function to shorten the weak secret key and reduce the amount of information obtained by Eve as much as possible. By sacrificing partially key information of Alice and Bob, privacy amplification makes the knowledge obtained by Eve been meaningless.

Though the majority researches (such as [START_REF] Watanabe | Privacy amplification for quantum key distribution[END_REF][START_REF] Renner | Universally Composable Privacy Amplification Against Quantum Adversaries, Theory of Cryptography[END_REF]) about privacy amplification focusing on the theoretical study and proof of security, implementing an efficient privacy amplification scheme in QKD system has been more and more significant.

In this paper, we propose a real-time privacy amplification scheme (RTPA) and implement RTPA in CLIP system [START_REF] Zou | CLIP: A Distributed Emulation Platform for Research on Information Reconciliation[END_REF], which is connected to the quantum communication system. After extensive experiments, the performance and the detail analysis are described in Section III. Experimental results show the efficiency of our proposed RTPA scheme for generating unconditional security keys in quantum cryptography.

2

The Proposed RTPA Scheme

Privacy Amplification Protocol

After analyzed and researched the classical and quantum privacy amplification theoretical study in [START_REF] Bennett | Generalized privacy amplification[END_REF][START_REF] Chandran | Privacy amplification with asymptotically optimal entropy loss[END_REF][START_REF] Dodis | Non-malleable extractors and symmetric key cryptography from weak secrets[END_REF][START_REF] Horvá | Effective privacy amplification for secure classical communications[END_REF] and etc., we approach the RTPA protocol (Real-time Privacy Amplification Protocol).

We assume that the key information of Alice and Bob after information reconciliation is W and its length is N , the length of key information used for reconciliation, confirmation and etc. is K , the length of key information may obtained by Eve is T , the security parameter is S , and the final key length is R . We describe the RTPA protocol as follows:

 Alice and Bob select the security parameter

f , fF  , :{0,1} {0,1} NR F  , R N T K S     ;
 Alice and Bob gain the final key y , () y f W  .

In RTPA protocol, hash function f is randomly chosen from class 3 H of univer- sal 2 . The hash function is described by Toeplitz matrix construction method [START_REF] Mansour | The computational complexity of universal hashing[END_REF][START_REF] Krawczyk | LFSR-based hashing and authentication[END_REF][START_REF] Fung | Practical issues in quantum-keydistribution postprocessing[END_REF]. After applying the privacy amplification procedure, the final key is unconditionally safe to Eve.

2.2

The RTPA Scheme

The RTPA scheme mainly consists three parts: Hash function construction, data communication and privacy amplification. The architecture of RTPA is shown in Figure 1.

Hash function construction

As shown in Figure 1, the parameter controller carries out the security parameter

Experimental Results And Analysis

The RTPA scheme is implemented in CLIP [START_REF] Zou | CLIP: A Distributed Emulation Platform for Research on Information Reconciliation[END_REF] which is connected to the real quantum communication system. The experimental environment is shown in Figure 2. We conducted extensive experiments to evaluate the performance of RTPA. We analyzed the privacy amplification overhead, average bit error rate (avBER) of key information.

Privacy Amplification Overhead

Various hash function constructed for different input key lengths, will lead to different time overhead per privacy amplification process. While the input key length should be long enough in order to gain an absolutely security key, the privacy amplification overhead will be very high. In this experiment, we test the privacy amplification overhead of different hash function scale. The result is shown in Figure 3. For example, it will cost 0.19s/p (second per amplification process) when converting a key from 1600 bits to 800bits. Though costing 9.5 times overhead than the scale of 200*400, the security of keys is enhanced by thousands of times. The hash function scale should be balanced between the security demands and the time overhead.

Average Bit Error Rate

After the procedure of information reconciliation, Alice and Bob have own almost uniform keys with comparative low BER (Bit Error Rate). When applying hash func-tion to these keys, it may generate quite different strings for Alice and Bob. Therefore, we test the average Bit Error Rate for the final keys with different quantum channel Bit Error Rates.

As it shown in Figure 4, privacy amplification can work effectively when the BER of quantum channel is lower than 0.06. When the BER of quantum channel ranges from 0.06 to 0.10, the information reconciliation procedure still works effectively, the BER after information reconciliation is close to zero, but the BER after privacy amplification is very high. And it doesn't meaningless when the quantum channel BER is higher than 0.10.

Conclusion

In this paper, we approached the privacy amplification protocol and proposed the RTPA scheme, a real-time quantum privacy amplification procedure in QKD systems.

To evaluate the performance of RTPA, we built a prototype QKD system based on CLIP [START_REF] Zou | CLIP: A Distributed Emulation Platform for Research on Information Reconciliation[END_REF]. Experimental results showed the efficiency of our proposed RTPA scheme when the bit error rate of quantum channel is lower than 0.06. The results showed that the performance of RTPA is greatly affected by the quantum channel BER and the information reconciliation. In order to gain an efficient performance, we must enhance the performance of information reconciliation to gain a low BER of key information before privacy amplification.

S

  and controls the generation of Shift and Seed based on the quantum channel states. Then, the hash function construction module constructs Toeplitz hash function scaling NR  .

Fig. 1 .

 1 Fig. 1. The Architecture of RTPA

Fig. 2 .Fig. 3 .

 23 Fig. 2. The experimental environment of RTPA

Fig. 4 .

 4 Fig. 4. The Average Bit Error Ratios with different scenes

  Seed and the shift string Shift .

					Seed and Shift send to Bob
	through the public channel;
	 Alice	and	Bob	construct	the	hash	function

S , according to the quantum key state, key length N and other information;

 Alice generates the description information about hash function randomly, the seed string

The Corresponding author: Dr. Baokang Zhao, School of Computer Science, National University of Defense Technology.CHINA.

Acknowledgment The work described in this paper is partially supported by the grants of the National Basic Research Program of China (973 project) under Grant No.2009CB320503, 2012CB315906;the National High Technology Research and Development Program("863"Program) of China under Grant No. 2011AA01A103, the project of National Science Foundation of China under grant No. 61070199, 61003301, 61103189, 61103194, 61103182, 61202488; the Research Fund for the Doctoral Program of Higher Education of China uner Grant No. 20124307120032, and supported by Program for Changjiang Scholars and Innovative Research Team in University of the Ministry of Education(''Network Technology",NUDT), the Innovative Research Team in University of Hunan Province(''Network Technology",NUDT), and the Innovative Research Team of Hunan Provincial natural science Foundation(11JJ7003).


Xiaohui Kuang
email: xiaohui_kuang@163.comlixiang8358@hotmail.com

Xiang Li

Jinjing Zhao
email: misszhaojinjing@hotmail.com

Architecture of Network Environment for High-risk Security Experimentation

Keywords: security experimental environment, architecture, virtualization, characteristic analysis

Adequate Environment for conducting security experiments and test under controlled, safe, repeatable and as-realistic-as-possible conditions, are a key element for the research and development of adequate security solutions and the training of security personnel and researchers. In this paper, a new large-scale network experimental environment for high-risk security research was put forward. The main idea was using isolated computing clusters to obtain high levels of scale, manageability and safety by heavily leveraging virtualization technology, separating experiment and control network and multilayer sanitization.

Introduction

Experimentation is a keystone of scientific method and of technology innovation and development. The success of Internet can be attributed to many factors. However, experimentation environment played an important role. Today more and more researchers involved in designing network services, protocols and security mechanism rely on results from emulation environments to evaluate correctness, performance and scalability [START_REF] Maier | Experiences with node virtualization for scalable network emulation[END_REF][2][3] [START_REF] Simmonds | Towards Scalable Network Emulation[END_REF][5] [START_REF]Design and Implementation of a Simulation Environment for Network Virtualization[END_REF]] [7] .

To better understand the behavior of these applications and to predict their performance when deployed across the Internet, the emulation environments must closely match real network characteristics. But, these emulation environments pay attention to scalability, fidelity and flexibility, don't take into account about risk and sanitization. The high-risk experiments such as network worms, botnets, and viruses and so on, are difficult to conduct in these network emulation environments.

In this paper we describe a new architecture of network environment for conducting high-risk security experimentation. The key idea behind our environment is the use of isolated, special purpose computing clusters, which heavily use virtualization technology, physical and logical separation, and cluster management tools in order to attain a high level of scalability, flexibility, isolation, and sanitization. The main contribution of this paper is 1) to analyze the requirement of high-risk security experiment, 2) to describe the architecture of a large-scale network environment that match the requirement, 3) to analysis the characteristic of the environment, 4) to describe the test on the environment.

The rest of the paper is organized as follows: Section II presents the requirement of security research facilities should match. Section III describes the architecture of our experimental environment named LNESET (Large-scale Network Emulation environment for high-risk Security ExperimenTation), and the technical details of the actual testbed. We then give the analysis in Section IV. Finally, our conclusions are in Section V.

2

Requirements for Security ExperimenTation environment

Risk Analysis and Risk Management

Depending on the kinds of research activities performed, security research can involve risks associated to the existing information infrastructure and ultimately to the public at large. From a confidentiality point of view, it is important to protect data from software vulnerabilities and malware collections from use for nefarious purposes. In addition, certain data collections that are used in security research, such as network traffic traces, could potentially contain private information. Similarly, details about network architecture or configuration of defensive mechanisms from real networks that are being emulated in a testbed facility should be protected from unauthorized access, as knowledge of these details could jeopardize their security. Most importantly, experiments involving live malware could "spill" into a real computing environment, affecting it from an integrity and availability point of view, for example, in the case of accidental releases of malware samples on previously uninfected machines. Alternatively, the effects of such actions could be indirect, such as those caused by researchers interacting with infected and criminal-controlled systems. In that case, this action could potentially trigger a premature and unnecessary arms race between the criminals and security researchers and security product vendors, by alerting cybercriminals that someone is "onto them", or on weaknesses in their tools and approaches.

Key Requirements Analysis

The construction of network experimental environment can be essentially conducted in four fashions: mathematical modeling, stochastic simulation, in laboratory emulations, or test-bed. The fidelity and scalability of the experimental environments built with different fashion are significantly different, and the laboratory emulation has often been the preferred method in security research, especially with regards to malware analysis. Laboratory experimentation offers an interesting compromise. On the one hand, the controlled conditions in which they are ideally conducted provide 1) the ability to validate previous experimental results obtained by others, i.e. repeatability, and 2) the ability to vary the parameters and characteristics of security solutions or threats being studied, i.e. experimental control. On the other hand, the use of the same or similar pieces of hardware (whether real or emulated) and the same software that is present in the real world, whether offensive or defensive, adds a level of a priori realism that is hard to attain just by modeling and simulation. However, in order to conduct security experiment, the emulation environment must obey the following criteria:

Scale. The number of elements (machines, subnets, etc.) that are being emulated or recreated in the experiment should be large enough to approach the numbers in the real world or at the very least large enough so that statistically significant results can be obtained.

Fidelity. The static conditions describing the environmental setup should be as close as possible to those of typical equivalent environments in the real world. This includes network topology, server configurations, proportion of machines and equipment in various roles, and security mechanism.

Isolation. Security experiments in emulation environment are often involving live malware, such as worm and virus, which could destroy the security of the other network, such as management network or data-collection network. So the environment should isolate the live malware from the other network.

Sanitization. Even if the live malware could be isolated in experimental network, it can destroy subsequent experiment conducted in the environment. So, the experimental environment should sanitize machines and network nodes quickly and entirely.

3

Architecture of security experimental environment

Main idea

According to the requirement of security experiments, the LNESET are built on clustering, virtualization, and software routing technology. The architecture of LNESET is detailed in Fig. 1, and is basically composed of three layers; they are physical infrastructure layer, Meta resource layer, and Experiment layer.

physical infrastructure layer

At the lowest layer is the physical infrastructure layer, which is composed of compute nodes, switches, and other physical resources that is similar to the Emulab suite. The physical infrastructure of LNESET consists of two components: the control network and experimental network.

The control network consists of a management server and the data server, the former is responsible for the centralized management, configuration and monitoring of the hardware and software resources in the experimental environment. Besides, it provides a user interface to the researchers to configure, run, monitor the environment, furthermore collect and analyze the experiment results. The data server is used to store a variety of virtual image files and experimental data.

The experimental network is made up of various types of experiment nodes which are interconnected with the programmable network. The programmable network is stacked with some high-speed Ethernet switches which support VLAN partitioning. The experiment nodes include computer cluster, real router, real terminal and real network.

control network and experimental network are isolated by MLS authentication and access control mechanism, which is very import for security experiment. It allows only a set of predefined information to flow between the control network and experimental network, which is needed to manage, configure, and sanitize the experimental network. Any other information will be denied to translate from experimental network to control network.

Meta resource layer

The meta resource layer is composed of a subset of resources allocated from the physical resource layer as needed by the experiment. After the requested resources have been successfully allocated by the control network, LNESET will bootstrap each compute cluster node by running a customized OS image that supports VMs. The meta resources include not only real terminal, router and network connectivity between them, but also emulation resources which are constructed by virtualization on computer cluster node. These emulation resources include emulation network, router, terminal and link. LNESET realize the emulation network by extending NS2 [8] , realize emulation router by extending Quagga [9] , and realize emulation Link by extending TC in Linux kernel [10] . In order to improve the scalability of computer cluster, LNESET use Xen [11] and OpenVZ [12] , which could emulate one hundred nodes on one computer.

Meta resources are managed by LNESET. LNESET translates the experiment specification into meta resource requirements and instructs to allocate the resources for the experiment. After experiment, LNESET could retrieve resources by management server. In order to clear the live malware, the computer cluster node will reboot remotely on initial stage of each experiment, which will format the local disk. After that, LNESET will reload different emulation image from data server according experimental requirement, which will emulate network, router, terminal or link.

Experiment layer

The experiment layer is created according to the network model of the experiment. Each compute cluster node serves as a basic scaling unit and implements the operation of emulation network, emulation terminal or emulation router that is mapped to it. A scaling unit for a network consists of a simulator instance and zero or more emulated hosts each running as a VM. An emulated host can also run directly on a physical compute node. This is designed for cases where the emulated hosts have stronger resource requirements and thus cannot be run as VMs. LNESET provides an emulation infrastructure to connect the emulated hosts running on virtual or physical machines to the corresponding simulator instances.

After the experiment starts, the experimenter can interact with the emulated hosts and the simulated network entities. To access the emulated hosts, the experimenter can directly log onto the corresponding computing nodes or VMs and execute commands (e.g., pinging any virtual hosts). To access the dynamic state of the simulated network, LNESET provides an online monitoring and control framework. This allows the experimenter to query and visualize the state of the network.

analysis of architecture

According to the previous architecture description in detail, LNESET can match the requirement of high-risk security experiment. Scale. In LNESET, meta resources include emulation network, router, and terminal, which are realized by virtualization technology. Each computer cluster node can emulate network including one hundred node, such as router, terminal or server. So, LNESET could provide a large network environment for security experiment based on cluster, hence it has a better scalability.

Fidelity. In LNESET, except of real network, router and server, the emulation resources have high consistency with real resources. Based on virtualization technology, emulation resource could provide a realistic operating environment for testing real implementations of network protocol, applications and services. The routers, terminals and servers, and the connectivity between them could be configured according the experiment requirement. The network layer and system layer topology and network flow of environment could configure dynamically, so LNESET also provide a high level fidelity than test-bed based on simulation or analysis model.

Isolation. Because the MLS authentication and access control mechanism only allows very specific requests to proceed, the control network has very little interaction with the experimental network, so that it is not generally susceptible to attacks or malicious activities carried out by the security experiment such as worm or virus.

Sanitization. In LNESET, every resource will be initialized at the beginning of experiment. The experimental node include real node and cluster node will be sanitized entirely, because they reboot over network, and the boot files in server cannot rewrite. After reboot, the local disks of these experimental nodes will be formatted clearly. Every real router will be reset at the initial stage. So LNESET should sanitize all resources entirely.

Conclusion

Based on the in-depth analysis of the requirements of environment for high-risk experiment, in this paper we propose an emulation experimental environment named LNESET. We describe the architecture of LNESET in detail. LNESET supports highlevel isolate between control network and experimental network, provides the necessary tools for the experimenters to allocate and reclaim the resources. The resources may consist of the compute nodes in the cluster and real machines or routers. Each compute node is treated as a scaling unit in LNESET; it can be configured as an emulation network with a set of VMs, a router or terminal for emulated hosts. The latter provides a realistic operating environment for testing real implementations of network applications and services. The VMs are connected with the simulator instances using a flexible emulation infrastructure. The analysis shows that LNESET is effective for high-risk security experimentation.

Fig. 1 .

 1 Fig. 1. The Architecture of Large-scale Network Emulation Environment for High-risk Security Experimentation

Acknowledgment

This research is supported by National Natural Science Foundation of China (Grant No. 61100223).


Jinjing Zhao
email: misszhaojinjing@hotmail.com

Yan Wen

Emulation on the Internet Prefix Hijacking Attack Impaction

Keywords: IP prefix hijacking, Power law, BGP, Inter-domain routing system, Internet emulation environment

There have been many incidents of IP prefix hijacking by BGP protocol in the Internet. Attacks may hijack victim's address space to disrupt network services or perpetrate malicious activities such as spamming and DoS attacks without disclosing identity. The relation between network topology and prefix hijacking influence is presented for all sorts of hijacking events in different Internet layers. The impaction parameter is analyzed for typical prefix hijacking events in different layers. A large Internet emulation environment is constructed and the attack impaction of IP prefix hijacking events are evaluated. The results assert that the hierarchical nature of network influences the prefix hijacking greatly.

Instruction

Prefix hijacking is also known as BGP hijacking, because to receive traffic destined to hijacked IP addresses, the attacker has to make those IP addresses known to other parts of the Internet by announcing them through BGP. Because there is no authentication mechanism used in BGP, a mis-behaving router can announce routes to any destination prefix on the Internet and even manipulate route attributes in the routing updates it sends to neighboring routers. Taking advantage of this weakness has become the fundamental mechanism for constructing prefix hijack attacks. They occur when an AS announces a route that it does not have, or when an AS originates a prefix that it does not own. Previous efforts on prefix hijacking are presented from two aspects: hijack prevention and hijack detection. Generally speaking, prefix hijack prevention solutions are based on cryptographic authentications [START_REF] Subramanian | Listen and whisper: Security mechanisms for BGP[END_REF][START_REF] Ng | Extensions to BGP to Support Secure Origin BGP[END_REF][START_REF] Kent | Secure border gateway protocol (S-BGP)[END_REF][START_REF] Zhao | Aggregated path authentication for efficient bgp security[END_REF][START_REF] Smith | Securing the border gateway routing protocol[END_REF] where BGP routers sign and verify the origin AS and AS path of each prefix. While hijack detection mechanisms [START_REF]Routing information service: myASn System[END_REF][START_REF] Lad | PHAS: A prefix hijack alert system[END_REF][START_REF] Qiu | Efficient techniques for detecting false origin advertisements in interdomain routing[END_REF][START_REF] Karlin | Pretty good bgp: Protecting bgp by cautiously selecting routes[END_REF][START_REF] Xu | MIRO: multi-path interdomain routing[END_REF][START_REF] Hu | Accurate Real-time Identification of IP Prefix Hijacking[END_REF][START_REF] Zheng | A Light-Weight Distributed Scheme for Detecting IP Prefix Hijacks in Realtime[END_REF] are provided when a prefix hijack is going to happening which correction steps must follow. Because there is a lack of a general understanding on the impact of a successful prefix hijack, it is difficult to assess the overall damage once an attack occurs, and to provide guidance to network operators on how to prevent the damage.

In this paper, we conduct a systematic study on the impaction prefix hijacks launched at different position in the Internet hierarchy. The Internet is classified into three hierarchies-core layer, forwarding layer and marginal layer based on the commercial relations between autonomous systems (ASes). And a large Internet emulation environment is constructed which hybridizes the network simulation technology and packet-level simulation technology to achieve a preferable balance between fidelity and scalability. The experiment results show that the hierarchical nature of network influences the prefix hijacking greatly.

The remainder of this paper is organized as follows: The related works are discussed in section 2. The impaction analysis of the prefix hijacks attack is presented in section 3, in which IP prefix hijacks are classified on a comprehensive attack taxonomy relying on the Internet hierarchy model and BGP protocol policies. Section 4 builds an emulation environment to test the correctness of our conclusion and section 5 concludes the paper.

Related work

Various prefix hijack events have been reported to NANOG [START_REF]The NANOG Mailing List[END_REF] mailing list from time to time. IETF's rpsec (Routing Protocol Security Requirements) Working Group provides general threat information for routing protocols and in particular BGP security requirements [START_REF] Christian | BGP Security Requirements[END_REF]. Recent works [START_REF] Butler | A Survey of BGP Security Issues and Solutions[END_REF][START_REF] Goldberg | How Secure are Secure Interdomain Routing Protocols?[END_REF] give a comprehensive overview on BGP security. The prefix hijacking is one of the key problems being noticed to BGP in these papers.

Previous works on prefix hijacking can be sorted into two categories: hijack prevention and hijack detection. The former one is trying to prevent the hijacking in the protocol mechanism level, and the latter one is trying to find and alert the hijacking event after it happening. The methods adopted can be categorized into two types: cryptography based and non-crypto based.

3

Analysis on Prefix Hijack Attack Impaction

Internet Hierarchy

In [START_REF] Zhu | An efficient Algorithm on Internet Hierarchy Induction[END_REF], we build a three-hierarchy model of the Internet and give an efficient arithmetic for it. The model is organized as follows:

a)

The set of nodes who have no providers forms a clique (interconnection structure), which is the core layer.

b) If the nodes don't forward data for others, then it belongs to the marginal layer.

c)

The node that belongs to neither the core layer nor the marginal layer belongs to the forwarding layer. And the forwarding layer has several sub-layers.

The relation between prefix hijacking and the Internet Hierarchy

For the simpleness of the description, the ASes whose prefixes being hijacked are expresses with V, and the hijack attack ASes are denoted by A. Furthermore, we suppose each AS only has one provider. The multi-home mechanism is not considered in this paper.

To evaluate the influence if prefix hijacking events, two impaction parameters are introduced as follows:

Definition 1 Set of the affected nodes Nc: The set of nodes whose routing states might be changing because of the happening prefix hijacking event.

Definition 2 Affected path factor µ: The percentage of the paths might be changed because of the happening prefix hijacking event.

In paper [START_REF] Zhao | The Relation on Prefix Hijacking and the Internet Hierarchy[END_REF],we classified the prefix hijacking events into nine types according to the different positions which the attackers and victims are located. The relation between prefix hijacking and the Internet hierarchy are concluded by the two impaction parameters .

From the analysis, these results can be drawn:

1) The hijacked AS in the core layer is not the most awful thing. On the contrary, if the AS in the marginal layer being hijacked, the number of the affected nodes is the largest among the three levels;

2) The hijacked AS in the forwarding layer can affect more paths than the core layer or the marginal layer;

3) If the hijacked ASes are in the same level, the hijacking AS in the forwarding layer can affect more nodes than the core layer or the marginal layer, and the higher attacker is in, the larger its influence will be;

4) The sub-prefix hijack can affect more ASes than the same prefix hijack, and the lager sub-prefix range is, the bigger affected path factor µ will be.

Evaluation Environment and Experiment

In order to verify the correctness of the conclusions in section 3, we build a prefix hijacking attack emulation environment, which is composed of three Juniper J2350 routers and four server computers. Each server can emulate 30 virtual routers.

For the authenticity of the test, the real BGP data is samples for the topology of inter-domain system. According to the sampling rules in [22], a network with 110 ASes is build, and the commercial relations are reserved. The network is also be classified into layers by the hierarchical algorithm in section 3.

Each prefix hijacking cases, we repeat the attach process three times, and calculate the average values of the affected nodes number Nc and path factor µ. The results are described in Table 1.

From the expariment results, we can see that if the AS in the marginal layer being hijacked, the number of the affected nodes is the largest among the three levels; the hijacked AS in the forwarding layer can affect more paths than the core layer or the marginal layer; and the hijacking AS in the forwarding layer can affect more nodes than the core layer or the marginal layer.

Conclusion

This paper conducts a systematic study on the impaction prefix hijacks launched at different position in the Internet hierarchy based on the work in paper [START_REF] Zhao | The Relation on Prefix Hijacking and the Internet Hierarchy[END_REF]. A large Internet emulation environment is constructed which hybridizes the network simulation technology and packet-level simulation technology to achieve a preferable balance between fidelity and scalability. The experiment results show that the hierarchical nature of network influences the prefix hijacking greatly.

Table 1 .

 1 Experiment Results

	Case	Nc	µ
	VC, AC	13	43
	VC, AF	24	53
	VC, AS	18	36
	VF, AC	28	118
	VF, AF	34	78
	VF, AS	21	62
	VS, AC	32	75
	VS, AF	57	73
	VS, AS	28	65

Acknowledgment

This research is supported by National Natural Science Foundation of China (Grant No. 61100223).


Lu Zhao

Ho-Seok Kang

Sung-Ryul Kim

Improved Clustering for Intrusion Detection by Principal Component Analysis with Effective Noise Reduction

Keywords: Intrusion detection, Principle Component Analysis (PCA), effective noise reduction, GA-KM

. In GA-KM [2], we have proposed GA-KM algorithm and have experimented using KDD-99 data set. The result showed GA-KM is efficient for intrusion detection. However, due to the hugeness of the data set, the experiment needs to take a long time to finish. To solve this deficiency, we combine PCA and GA-KM in this paper. The goal of PCA is to remove unimportant information like the noise in data sets which have high dimension, and retain the variation present in the original dataset as much as possible. The experimental results show that, compared to GA-KM [2], the proposed method is better in computational expense and time (through dimension reduction) and is also better in intrusion detection ratios (through noise reduction).

Introduction

With rapid growth of network-based services, network security is becoming more and more important than ever before. Therefore, intrusion detection system (IDS) [START_REF]Intrusion detection system[END_REF] plays a vital role in network security. There are two main categories of intrusion detection techniques: signature-based detection and anomaly-based detection. Signaturebased detection is also called misuse detection which is based on signatures for known attacks. Anomaly-based detection is different from signature-based detection, which is able to detect unknown attacks by learning the behavior of normal activity.

In the training phase of this approach, IDS builds a profile which represents normal behavior. In the detection phase, the similarity of a new behavior with the profile is analyzed by IDS. If the new behavior is far from normal behavior of the profile, then this behavior will be labeled as an attack. We have proposed GA-KM algorithm [START_REF] Zhao | K-means Clustering by Genetic Algorithm for Anomaly-based Intrusion Detection[END_REF], and have experimented with this algorithm using KDD--99 data set, the results show that it is efficient for anomaly-based intrusion detection [START_REF] Denning | An Intrusion Detection Model[END_REF]. However, when we experiment with this algorithm, it takes a long time to finish. In this paper, to solve this deficiency, Principal Component Analysis is combined with GA-KM algorithm and is experimented on KDD-99 data set. PCA (Principal Component Analysis) can be used to reduce the dimension of high dimensional data and remove noise from it effectively. So we can use PCA algorithm to do some noise reduction on KDD-99 data. The experimental results show that the propose method reduces the training time and testing time greatly, and also is efficient for intrusion detection.

The rest of this paper is organized as follow: in section 2, we will introduce previous works. Section 3 describes proposed method. In section 4, we report our experimental results and evaluations. Finally, in section 5, we conclude this paper.

2

Related work

GA-KM algorithm

GA-KM algorithm [START_REF] Zhao | K-means Clustering by Genetic Algorithm for Anomaly-based Intrusion Detection[END_REF] combines genetic algorithm into the traditional K-means clustering algorithm [START_REF] Kaufan | Finding groups in data: an introduction to cluster analysis[END_REF]. In GA-KM algorithm, each individual consists of a certain number of cluster centers. The value of each cluster center is called gene of individuals. And a fitness function is defined as follows:

) 1 /( 1 ) ( c J x f   (1)
where c J is the object function for K-means algorithm. We use this fitness function to evaluate each individual in a population. It means that if c J is the small, the fitness value is the greater, and the clustering result is better.

In GA-KM, selection, crossover and mutation operators are a little different from original GA.

 Selection

We combine elitism selection and fitness proportionate selection [START_REF]Selection for genetic algorithm[END_REF] to increase the performance of GA-KM. Elitism selection first retains the best individual which has the best fitness value in current population, and then replaces the worst individual in new population with the best individual which is retained in current population.

 Crossover

To obtain better individuals and increase convergence speed of GA-KM, good individuals which have big fitness values cross over their genes among themselves and bad individuals which have small fitness values cross over their genes in arithmetic crossover method among themselves.

The selections of genes depend on two cluster centers' distance for two individuals, one cluster center for one individual. We first calculate the distance of all pairs of cluster centers each from two individuals, and then match up cluster centers based on their minimum distance and cross over the values of these two cluster centers.

In the formula (2), (2)  Mutation In this stage, the genes of bad individuals could have bigger chance of mutation than the genes of good individuals. So, in order to prevent early mature convergence and generate newer mutation of individuals, the genes of good individuals are modified based on original genes with a small value Min, and the genes of bad individuals are modified on original genes with a big value Max.

Principal Component Analysis

PCA (Principal Component Analysis Algorithm) known as dimension reduction technique is a useful method for identifying patterns in complex data of high dimensions, and expressing the data in such a way as to highlight their similarities and differences [START_REF] Lowden | Network Intrusion detection by using Feature Reduction Technique[END_REF]. And this method can effectively identify data "main" elements and structure, remove noise and redundancy, and reveal the simple structure hidden in complex data.

3

Our proposed method

Data Description

For our experiments we use KDD-Cup 1999 dataset [START_REF]The third international knowledge discovery and data mining tools competition dataset\[END_REF]. KDD-Cup 1999 data set contains a wide variety of intrusions simulated in a military network environment which is used for the Third International Knowledge Discovery and Data Mining Tools Competition. Each example in the data is a record of extracted features from a network connection gathered during the simulated intrusions. A connection is a sequence of TCP packets which data flows to and from a source IP address to a target IP address under some well-defined protocol. Each connection record consists of 41 fields which contain basic features about TCP connection as duration, protocol type, number of bytes transferred, domain specific features as number of file creation, number of failed login attempts, and whether root shell was obtained. Each connection is labeled as either normal, or an attack, with exactly one specific attack type.

Using PCA algorithm

In this paper, the goal of PCA algorithm is to reduce unimportant information of data set which have high dimension and retain the variation present in the original dataset as much as possible. Using PCA algorithm to reduce the dimensionality of complex data can decrease computing time when we use huge data. We use PCA algorithm to do effective noise reduction for data set S which are In the above three tables, scaling means zero-mean normalization method which is used to preprocess data set. And all distances means the minimum distance between cluster center and data. Normal represents the minimum distance between cluster center and normal data from testing data; Attack represents the minimum distance between cluster center and attack data; Ratio1 is the value which is equal to Attack divided by Normal; Ratio2 is the value which is equal to Ratio1 for PCA with GA-KM divided by Ratio1 for GA-KM with scaling. If the value Ratio1 is bigger, the difference between normal data and attack data is more evident, and detecting attack is easier. In other words, if the value Ratio2 is bigger, the performance of PCA with GA-KM is better than GA-KM with scaling.

1 1 1 1 ' * ' * ) 1 ( ' ' * ) 1 ( ' * ' B r A r B B r A r A      
In the experiments, we use three kinds of distances to compare the performance of proposed method and GA-KM. As shown in Table 1, we use average distance to compare PCA with GA-KM, GA-KM with scaling, GA-KM without scaling; the results show that the performance of PCA with GA-KM is 1.37 times better than GA-KM with scaling. As shown in Table 2, we remove the extreme distance and then calculate the average distance to compare these two methods, the value Ratio2 is 1.12, the result shows that the performance of proposed method is 1.12 times better than GA-KM with scaling. In Table 3, we use median distance; the result also shows that the performance of PCA with GA-KM is better than GA-KM with scaling. Also from the tables, we also can know that the performance of PCA with GA-KM, GA-KM with scaling are better than GA-KM without scaling.

From these results, we can know that performance of proposed method outperforms GA-KM. So we can know that after using PCA, the proposed method can reduce noise data effectively and retain the variation present in the original dataset as much as possible. Meanwhile, it also can retain a good performance after effective noise reduction. As a result the proposed method is also acceptable for intrusion detection.

Conclusion

Our research work is based on intrusion detection. We use KDD Cup 99 dataset to experiment and find some redundant and irrelevant data like noise data in KDD Cup 99. So to remove unimportant data effectively, we combine dimension reduction technique which is PCA algorithm with clustering method GA-KM. The goal of PCA is to reduce noise data effectively to get smaller dimensionality dataset from KDD Cup 99 dataset. Our research is to observe how Principal Component Analysis and GA-KM algorithm are used for intrusion detection. And when after the noise information of original dataset are reduced, how the performance is. The experimental results showed that the proposed method can give better and robust representation of data after effective noise reduction and have 42.5% ~ 80.7% time reduction in training, and also can retain a good performance. So, our proposed method is efficient and reliable for intrusion detection.

Table 1 .

 1 Comparison with average distance

		PCA with GA-	GA-KM with	GA-KM without
		KM	scaling	scaling
	Normal	1145.82495	3.143096903	1219.20607
	Attack	1900.862749	3.796500426	1445.27273
	Ratio1	1.66	1.21	1.19
	Ratio2		1.37

r

Table 2 .

 2 Comparison with average distance with extreme cases removed

		PCA with GA-	GA-KM with	GA-KM without
		KM	scaling	scaling
	Normal	1145.82495	3.143096903	1219.20607
	Attack	1535.489161	3.225661856	1210.45372
	Ratio1	1.34	1.02	0.99
	Ratio2		1.12

Table 3 .

 3 Comparison with median distance

		PCA with GA-	GA-KM with	GA-KM without
		KM	scaling	scaling
	Normal	1108.653748	2.764393351	1109.26483
	Attack	1359.351694	3.197027967	1213.48725
	Ratio1	1.23	1.15	1.09
	Ratio2		1.07

preprocessed by mapped. Here, data set S are represented as a N D matrix, in the matrix, each column represents one data example of dataset; N is the number of data examples, D is the number of dimensionality for each connection record.

Firstly, calculate the mean value of all data examples:

Secondly, subtract mean vector for each data example:

Thirdly, find covariance matrix  of data set S , and then calculate all eigenvec- tors and eigenvalues of  ;

Experiment Results and Evaluations

In this section, we detail the experiment results of the proposed algorithm and evaluate the performance of proposed method. We experimented with this proposed method using KDD Cup 99 dataset in our paper. For training and developing normal clusters, data file "kddcup.data_10_percent" which is downloaded from KDD Cup 1999 site is used for our experiments. The training data set consists of normal data selected from the file "kddcup.data_10_percent". And the testing data set consists of normal data and attack data which are selected from the file "corrected". The main goal of our experiment is to study how the performance of proposed method.

In our experiments, we use two kinds of data sets which are original KDD CUP 99 dataset and KDD CUP 99 dataset preprocessed by PCA algorithm with effective noise reduction. In [START_REF] Zhao | K-means Clustering by Genetic Algorithm for Anomaly-based Intrusion Detection[END_REF], we have proved that GA-KM algorithm is efficient for anomalybased intrusion detection. Our experimental results showed that the proposed method gives better representation of data set after removing noise data, and approximately 42.5% ~ 80.7% reduction in training time. Meanwhile, we compared the performance of improved clustering method with original GA-KM.


Giuseppe Cattaneo
email: cattaneo@dia.unisa.it

Giancarlo De Maio
email: demaio@dia.unisa.it

Pompeo Faruolo

Umberto Ferraro Petrillo

A Review of Security Attacks on the GSM Standard

Keywords: GSM, mobile security, security attacks, encryption

The Global Systems for Mobile communications (GSM) is the most widespread mobile communication technology existing nowadays. Despite being a mature technology, its introduction dates back to the late eighties, it suffers from several security vulnerabilities, which have been targeted by many attacks aimed to break the underlying communication protocol. Most of these attacks focuses on the A5/1 algorithm used to protect over-the-air communication between the two parties of a phone call. This algorithm has been superseded by new and more secure algorithms. However, it is still in use in the GSM networks as a fallback option, thus still putting at risk the security of the GSM based conversations. The objective of this work is to review some of the most relevant results in this field and discuss their practical feasibility. To this end, we consider not only the contributions coming from the canonical scientific literature but also those that have been proposed in a more informal context, such as during hacker conferences.

Introduction

The GSM is the most widespread mobile communication technology, accounting for more than five billion subscriptions. Far from being just a personal communication technology, it has become the medium of choice for implementing and delivering a vast array of services ranging from mobile banking applications to electronic ticketing. This widespread use is also motivating the interest of researchers in evaluating the security mechanisms provided by GSM to protect user communication. In particular, the GSM protocols suffer from many weakness which allowed for the development of several attacks able to break confidentiality and privacy of subscribers. GSM carriers seem to have underestimated these threats, as witnessed by the several solutions for providing security to GSM-based communications (see [START_REF] Castiglione | SECR3T: Secure End-to-End Communication over 3G Telecommunication Networks[END_REF][START_REF] Castiglione | Engineering a secure mobile messaging framework[END_REF][START_REF] De Santis | An Extensible Framework for Efficient Secure SMS[END_REF][START_REF] Gsmk | Cryptophone[END_REF]) proposed so far. The objective of this paper is to review some of the most relevant security attacks to the GSM related technologies, including also those techniques that, although not being presented in a formal scientific context, have proved to be very effective in practice.

The GSM Standard

The GSM has been developed by the ETSI as a standard [START_REF]3rd Generation Partnership Project (3GPP): Technical Specifications for GSM systems[END_REF] to describe protocols for second generation digital cellular networks used by mobile phones. It offers several services based on voice transmission and data transmission. Three are the main elements of a GSM network. The first is the Mobile Station. It is made up of the Mobile Equipment (ME), the physical phone itself, and the Subscriber Identity Module (SIM). The SIM is a smart card that carries information specific to the subscriber together with the encryption keys (Ki and Kc). The second element is the Core Network. It carries out call switching and mobility management functions for mobile phones roaming on the network of base stations. It is made of several components. The third element is the Base Station Subsystem. It is responsible for handling traffic and signaling between a mobile station and the core network.

Security Features

The GSM standard defines several security mechanisms for protecting both the integrity of the network and the privacy of the subscribers. Whenever a ME tries to join a GSM network, it has to pass through an authentication procedure required to verify the identity of the subscriber using it. This denies the possibility for a subscriber to impersonate another one and guarantees that only authorized subscribers may access the network. When connected, the signaling and data channels over the radio path between a base station and the ME are protected by means of an encryption scheme. This ensures the confidentiality of the conversations. In the following we provide more details about these schemes and about the cryptographic machinery they use.

Authentication. The GSM network authenticates the identity of a subscriber using a challenge-response mechanism. Firstly, the Authentication Center (AuC), located within the core network, generates a 128bit random number (RAN D) and sends it to the ME. Then, the ME computes the 32-bit signed response (SRES) based on the encryption of RAN D with the authentication algorithm (A3) using the individual subscriber authentication key (Ki). The computation is entirely done within the SIM. This provides enhanced security, because the confidential subscriber information such as the individual subscriber authentication key (Ki) is never released from the SIM during the process. On the network, upon receiving the signed response (SRES) from the subscriber, the AuC compares its value of SRES with the value received from the ME.

If the two values match, the authentication is successful and the subscriber joins the network. Notice that GSM authenticates the user to the network and not vice-versa. So, the security model offers confidentiality and authentication, but not the non-repudiation.

Data Confidentiality. The SIM contains the implementation of the key generation algorithm (A8) which is used to produce the 64-bit ciphering key (Kc) to be used to encrypt and decrypt the data between the ME and the base station. It is computed by applying the same random number (RAN D) used in the authentication process to the ciphering key generating algorithm (A8) with the individual subscriber authentication key (Ki). Additional security is provided by the periodic change of the ciphering key. Similarly to the authentication process, the computation of the ciphering key (Kc) is done within the SIM. Encrypted communications between the MS and the network is done using one of the A5 ciphering algorithms. Encrypted communication is initiated by a ciphering mode request command from the GSM network. Upon receipt of this command, the mobile station begins encryption and decryption of data using the selected ciphering algorithm and the ciphering key (Kc). The A5 algorithms are implemented in the hardware of the ME, as they have to encrypt and decrypt data on the fly.

The A5 Ciphering Algorithms. In the GSM protocol, the data is sent as sequence of frames, where each frame contains 228 bit. Each plaindata frame is XORed with a pseudorandom sequence generated by one of A5 stream cipher algorithms for ensuring over-the-air voice privacy. The A5/1 algorithm was developed in late 1987 and is based on three linear feedback shift registers (LFSR). The keystream is built by running an algorithm, called clock, that produces 1 bit at each step. The output of the algorithm is the XOR of the leftmost bit of the three LFSR registers. Each register has a clocking bit. At each cycle, the clocking bits of the registers are given as input to a function that computes the majority bit. A register is clocked if the clocking bit agrees with the majority bit. The A5/2 algorithm was introduced in 1989, it is a deliberate weakened version of the A5/1 that is almost identical to its counterpart except for an additional LFSR used to produce the three clocking bits. Since 2007, A5/2 is not implemented anymore in mobile phones for security reasons. Finally, the A5/3 algorithm was developed in 1997 and is based on the MISTY cipher [START_REF] Matsui | New Block Encryption Algorithm MISTY[END_REF]. In the 2002 it was modified in order to obtain a faster and more hardware-friendly version, called KASUMI [START_REF]3rd Generation Partnership Project (3GPP): Technical Specifications for GSM systems[END_REF].

Attacks

There is a wide category of attacks against mobile communications that do not depend on network weaknesses. It includes mobile phones malware, identity theft by SIM cloning and so on. Some other attacks, such as phishing with SMS, may exploit human factors as well. A good review of such security issues can be found in [START_REF] Castiglione | Do you trust your phone?[END_REF]. On the contrary, this work focuses on attacks that exploit vulnerabilities of GSM protocols.

Most of these attacks target the A5 family of ciphering algorithms. The exact formulation of these algorithms is still officially secret. However, the research community has been able to recover it through a mix of reverse engineering and cryptoanalysis. Namely, the general design of A5/1 was leaked in 1994 and the first cryptanalysis of A5/1 has been performed by Golic [START_REF] Golic | Cryptanalysis of Alleged A5 Stream Cipher[END_REF]. In this section we review some of the most interesting attacks proposed so far, distinguishing by passive and active attacks.

Passive Attacks

The first attack targeting the A5/1 algorithm has been proposed by Golic [START_REF] Golic | Cryptanalysis of Alleged A5 Stream Cipher[END_REF], which introduced an effective Time-Memory Trade-Off (TMTO) attack based on the birthday paradox. The basic idea of the TMTO is to pre-compute a large set of states A, and to consider the set of states B through which the algorithm progresses during the generation of output bits. Any intersection between A and B allows to identify an actual state of the algorithm. The proposed attack would be practicable only having 15 TB of pre-calculated data or 3 hours of known conversation [START_REF] Biryukov | Real time cryptanalysis of A5/1 on a PC[END_REF]. Biryukov et al. presented two attacks based on a TMTO [START_REF] Biryukov | Real time cryptanalysis of A5/1 on a PC[END_REF]. The first attack requires 2 minutes of known-conversation data and one second of processing time, while the second requires 2 seconds of plaintext data and several minutes of processing time. The amount of required storage is up to 290 GB. Unfortunately, its execution time grows exponentially with the decreasing of the input sequence. The attack exploits many weaknesses of A5/1, like the possibility of identifying states by prefixes of their output sequences, the ability to quickly retrieve the initial state of an intermediate frame and the possibility to extract the key from the initial state of any frame. The major drawback of this attack is the considerable amount of known-conversation data required. A different strategy, based on a correlation attack, was introduced by Ekdahl et al. [START_REF] Ekdahl | Another attack on A5/1[END_REF]. The main advantage is that whereas TMTO attacks have a complexity which is exponential with the shift register length, here the complexity is almost independent from it. This attack exploits the weakness that the key and the frame counter are initialized in a linear fashion, which enables to separate the session key from the frame number in binary linear expressions. This allows to decrypt a conversation in less than 5 minutes, provided that few minutes of plaintext conversation are available. Moreover, the time and space requirements for the tables precomputation are much smaller than in previous attacks. All the attacks presented so far had very high computational cost and/or were based on unrealistic assumptions. Instead, the first practicable attack, implementable by means of open-source software and commodity hardware, has been made public by Nohl in 2009 [START_REF] Nohl | Subverting the security base of GSM[END_REF]. This work showed that A5/1 is vulnerable to generic pre-computation attacks. In fact, for a cipher with small key (64 bit in the case of A5/1), it is possible to construct a code book. It can be exploited to perform a known-plaintext attack. For the case of A5/1, if an adequate number of plaintext/ciphertext couples are known, it is possible to recover the encryption key. In the case of GSM, a number of predetermined control messages can be leveraged as known plaintexts [START_REF] Nohl | Attacking phone privacy[END_REF]. Considering all the possible combinations, Nohl estimated that a code book for A5/1 would have been sized 128 PB and would have taken more than 100,000 years to be computed on a standard PC. In their talk, Nohl and Paget revisited techniques for computing the code book faster and for storing it compressed. They proposed a tweaked A5/1 engine optimized for parallelization. By using this technique a full code book for A5/1 can be computed in 3 months using commodity hardware. Some tweaks presented in subsequent talks [START_REF] Nohl | Attacking phone privacy[END_REF][START_REF] Paget | GSM: SRSLY? In: 26th Chaos Communication Congress[END_REF] allowed to lower this boundary to 1 month on 4 ATI GPUs. Moreover, he proposed the use of a combined approach for data storage which makes use of distinguished point and rainbow tables [START_REF] Lee | A comparison of perfect table cryptanalytic tradeoff algorithms[END_REF], by means of which it is possible to reduce the size of the code book to just 2 TB. Nohl estimates that the attack has a 99% success rate when data from a phone registered to the network can be collected, which maximizes the amount of known control frames. Otherwise, the success rate drops to 50%, since only a small number of frames with known plaintext is available. In a subsequent talk, Nohl and Munaut performed a demonstration on how it is possible to find phones and decrypt their calls [START_REF] Nohl | Wideband GSM sniffing[END_REF].

Active Attacks

Differently from passive attacks, active attacks exploit some design weaknesses of the telecommunication infrastructure which make possible to introduce a false mobile tower controlled by the attacker. The major security hole exploited by the fake tower, also called IMSI Catcher, is that the GSM specification does not require authentication of the network to the mobile phone. The IMSI Catcher acts between the victim mobile phone(s) and the real towers provided by the service provider, and it is able to both control communication parameters, like encryption algorithms, and eavesdrop traffic. Such an attack falls into the category of Man-In-The-Middle (MITM) attacks. Some MITM attacks against GSM have been introduced in [START_REF] Barkan | Instant ciphertext-only cryptanalysis of GSM encrypted communication[END_REF]. They suppose that the victim is connected to a fake base station, which is able to intercept and forward the data sent by the phone to the network and vice versa. At this point, independently from the encryption algorithm chosen by the network, the attacker can request the victim to use a weak cipher like A5/2 (or even no encryption). Then, the attacker can employ cryptanalysis of A5/2 to retrieve the encryption key. It is worth noting that the key generation algorithm only depends on the RAND parameter specified by the network. As consequence, the encryption key used between the victim and the attacker is the same used between the attacker and the network, so that the attacker can decrypt all the traffic even if a secure encryption algorithm like A5/3 is requested by the network. Paget and Nohl showed how it is possible to catch IMSI of a subscriber by means of an active attack [START_REF] Paget | GSM: SRSLY? In: 26th Chaos Communication Congress[END_REF]. Their attack makes use of a fake base station that could even be built from open source components. In 2010 a practical attack to GSM has been presented by Paget [START_REF] Paget | Practical Cellphone Spying[END_REF] using open source components. It exploits the vulnerability that the mobile phone connects to the strongest base station signal. Since the base station has full control over communication protocols, the handset can be instructed in order to use no traffic encryption (A5/0). In this way, the attacker can intercept all the traffic in plaintext.