Thomas Laurenson
email: thomas@thomaslaurenson.com

Performance Analysis of File Carving Tools

Keywords: File Carving, Data Recovery, Digital Forensics

File carving is the process of recovering files based on the contents of a file in scenarios where file system metadata is unavailable. In this research a total of 6 file carving tools were tested and reviewed to evaluate the performance quality of each. Comparison of findings to a previous similar study was conducted and showed variable performance advances. A new file carving data set was also authored and testing determined that the wider variety of file types and structures proved challenging for most tools to efficiently recover a high percentage of files. Results also highlighted the ongoing issue with complete recovery and reassembly of fragmented files. Future research is required to provide digital forensic investigators & data recovery practitioners with efficient and accurate file carving tools to maximise file recovery and minimise invalid file output.

Introduction

File carving is a particularly powerful technique because computer files can be recovered from raw data regardless of the type of file system, and file retrieval is possible even if the file system metadata has been completely destroyed [START_REF] Richard | Scalpel: A Frugal, High Performance File Carver[END_REF]. The process therefore provides additional data recovery methods to augment digital investigation where existing traditional data recovery techniques are not suitable or have been unsuccessful. Scenarios where file carving is exceptionally useful is when recovering data and files that have previously been deleted, extracting files from the unallocated space of a digital data storage device, and in cases when a storage device or a file system has been damaged or corrupted.

Previous research has advanced file carving techniques and algorithms resulting in newer state-of-the-art file recovery methods. Specifically, the Digital Forensic Research Workshop (DFRWS) conference promoted file carving techniques and tools by issuing a Forensic Challenge in 2006 1 and, again, in 2007 2 . The contests greatly extended file carving knowledge resulting in the discovery of new carving techniques and the release of associated tools.

Additionally, academic research has also contributed towards the improvement of file carving techniques, such as increasing file carving speed using GPUs [START_REF] Marziale | Massive Threading: Using GPUs to increase the performance of digital forensics tools: Digital Investigation[END_REF], advanced file structure carving for binary file types [START_REF] Hand | Bin-Carver: Automatic recovery of binary executable files[END_REF], and multimedia files [START_REF] Yoo | A Study on Multimedia File Carving Method: Multimedia Tools and Applications[END_REF]. Furthermore, methods have also been developed for scenarios including carving network packets; e.g. IP packets from forensic images [START_REF] Beverly | Forensic Carving of Network Packets and Associated Data Structures: Digital Investigation[END_REF] and carving file objects from memory dumps [START_REF] Van Baar | Forensic Memory Analysis: Files mapped in memory: Digital Investigation[END_REF]. Advanced file carving techniques have also been investigated including in-place file carving to reduce storage space and processing time [START_REF] Richard | In-Place File Carving[END_REF] and recovery and re-assembly of fragmented JPEG files [START_REF] Sencar | Identification and Recovery of JPEG Files with Missing Fragments: Digital Investigation[END_REF].

Problem

Digital Forensics is a relatively new discipline which presents numerous challenges for researchers and practitioners alike. Unfortunately, current research intended for forensic applications often has little or no impact, because in many instances the researchers are poorly acquainted with the real-world digital forensic problems encountered and the practical constraints frequently placed on investigators [START_REF] Walls | Effective Digital Forensics Research is Investigator-Centric[END_REF]. The solution is to conduct research which is investigator-centric with the aim of providing findings of practical usefulness lessening the gap between academic research and requisite real-world investigation tools and techniques. Furthermore, the targets of investigations are increasing in size and complexity [START_REF] Garfinkel | Digital Forensics Research: The Next 10 Years: Digital Investigation 7[END_REF]. Practitioners need informed results to confidently identify the correct tool for a specific scenario in order to decrease the overall case processing time while also maintaining investigation integrity.

File carving can be a difficult and complex process which is further complicated by the variety of available tools. Many forensic investigators are unaware of the capabilities and/or the limitations of the various file carving tools. Despite targeted active research a number of problems still exist for the professional digital forensic investigator or data recovery practitioner: which file carving tools provide the best performance in regards to 1) the percentage of files recovered; 2) the correctness and reliability of tool output; and 3) the processing speed of the tool.

This paper aims to provide digital forensic practitioners with practical information and recommendations to assist in reliable and thorough implementation of file carving techniques. An additional goal is to identify current weaknesses in file carving techniques and tools so that future research areas can be targeted for technology advancement.

Structure

Firstly, the basics of file carving is described in order to understand the subject matter. A tool testing methodology is then outlined including data sets, performance measurements and a thorough testing procedure. Carving tool results from the testing phase are reviewed and findings are discussed. Finally, conclusions are drawn and areas for future research are suggested.

File carving seeks to recover files based on content, irrespective of supporting file system metadata being available. The following subsections include a detailed summary of the various file structures, established file carving techniques and the associated file carving tools used by investigators to recover files in digital investigations.

File Structure

The structure of data in computer based systems is controlled by the file system allowing users the facility of long-term storage and retrieval of data in a hierarchy of files and directories [START_REF] Carrier | File System Forensic Analysis[END_REF]. Fig. 1 displays the 3 major types of file structures encountered: contiguous, fragmented and partial files. Embedded files are also discussed in this section.

Contiguous Files: A file is said to be contiguous when the data held in the file is stored in blocks in a logical order of sequence on the storage medium. The file is therefore stored in a single fragment occupying sequential file system clusters. A contiguous file (F ileA) is shown in Fig. 1, which occupies 3 consecutive blocks spanning from block 4 to 6. Fragmented Files: A file is fragmented when one or more chunks of the file are not stored in a sequential order and, thus, are comprised of two or more fragments separated from each other by an unknown number of clusters [START_REF] Pal | The Evolution of File Carving[END_REF]. As files are added, deleted or modified the structure of a file system becomes divided and files may not be stored on consecutive clusters. Fragmentation in hard disks is therefore a result of the file system's allocation strategy, usually to optimise techniques such as fast file access and increased storage efficiency [13].

Fragmented files have a variety of different forms. However, files with 2 fragments, known as bifragmented, have been recognised as being the most common [START_REF] Garfinkel | Carving Contiguous and Fragmented Files with Fast Object Validation: Digital Investigation[END_REF]. Fragmented files can be found in a linear and non-linear structure3 depending on where the separate fragments are stored on the file system. Fig. 1 displays a linear fragmented file (File B ) stored on a total of 5 blocks, separated by 3 blocks which are occupied by File A. The base-fragment of File B occupies blocks 1 to 3. For comparison, a non-linear fragmented file (File C ) is also shown, stored on a total of 6 blocks. The base-fragment of this file occupies blocks 14 to 16 while the second fragment occupies blocks 9 to 11.

The issue of file fragmentation and the potential occurrence in actual investigations is debated among digital forensic researchers and professionals. Analysis of 324 second-hand hard drives showed that a total of 6% of all files recovered were fragmented [START_REF] Garfinkel | Carving Contiguous and Fragmented Files with Fast Object Validation: Digital Investigation[END_REF]. Additionally, of all the fragmented files approximately 47% were discovered to be bifragmented. Although 6% seems a relatively small amount in general, it is highly significant that file types of forensic interest (e.g. AVI, DOC, JPG and PST) had considerably higher fragmentations than file types of little interest (e.g. BMP, HLP, INF and INI).

The availability and uptake of Solid State Drives (SSD) also has an impact on the level of fragmentation likely to be encountered. SSDs incorporate wearlevelling which results in files being moved more regularly and, although not yet proven, the probability is that SSDs would naturally be fragmented [START_REF] Pal | The Evolution of File Carving[END_REF].

Partial files: As the term implies, partial files are incomplete files where some portion of the file is unavailable. The reason why partial files exist is due to a fragment of the original file being overwritten by other data. Fig. 1 displays a partial file (File D) occupying blocks 12 and 13 which lacks a file footer.

Embedded Files: When the contents of one file are added or stored in another file it is known as an embedded file. A common example is a JPEG image embedded within a Microsoft Word document or files embedded in an archive file; e.g. ZIP files. Embedded files can be contiguous, fragmented or partial depending on the scenario.

File Carving Techniques

Previous research has identified various methods to perform file carving. An overview is provided outlining selected file carving techniques including headerbased, file structure and block-based carving, as well as the role of file validation in the file carving process.

Header-Based Carving: Files have unique headers, also known as magic numbers or file signatures. These unique values can be used to help identify the beginning of a file and aid in carving files without the corresponding metadata. Header-footer carving is the most basic carving technique which searches data for patterns that mark a distinct header (start of file marker) and footer (end of file marker) [START_REF] Tomar | Analysis Framework for Quality Measurement of Carving Techniques[END_REF]. The process is achieved by extracting all data contained within the headers and footers and copying that data into an external file.

An alternative header-based carving technique is header-maximum size carving. When a header is discovered (with no footer value available), the maximum carve size is used to calculate how far away from the header the end of the file might be [START_REF] Richard | Scalpel: A Frugal, High Performance File Carver[END_REF]. As some file types can vary dramatically in size, this technique can have varying results and can also increase the size needed to store recovered files. However, it remains a viable approach because many file formats (e.g. JPEG, MP3) are not affected if additional data is appended to the end of a valid file [START_REF] Garfinkel | Carving Contiguous and Fragmented Files with Fast Object Validation: Digital Investigation[END_REF]. Another header-based carving technique is header-embedded length carving. Some file formats have internal file information which specifies the length, or size, of the file and provides an identified point for the footer of the file [13].

File Structure Carving: Another file carving technique is based on the internal structure of a file, where specific knowledge of the contents can help reconstruct the original file. File structure carving is primarily aimed towards assembling fragmented files, where header-based carving fails to reconstruct multiple file fragments. An example is semantic carvers (also known as deep carvers) which use information about the internal file structure to control the carving process in some way [13].

Block-Based Carving: An advanced carving technique is block-based carving which calculates meta information of the content of a data block; for example, by implementing character counts or calculating statistical information [START_REF] Tomar | Analysis Framework for Quality Measurement of Carving Techniques[END_REF]. The premise is that computer systems use fixed block sizes (sectors) for storing data (usually 512 bytes) and file carvers can examine every block for every file type definition [START_REF] Metz | Analysis of 2006 DFRWS Forensic Carving Challenge[END_REF].

File Validation: The method of file validation is an integral aspect of the file carving process. Validation provides the confirmation that the carved data actually results in a valid file output. Therefore, an automated format validator is a function that accepts a block of data and then determines whether it conforms to the defined structure of the file format before resulting in a validated file [START_REF] Aronson | Towards an Engineering Approach to File Carver Construction[END_REF].

File Carving Tools

There is a wide selection of file carving tools available ranging from expensive proprietary forensic software suites (EnCase, FTK & WinHex) to open source software (Scalpel, Foremost & PhotoRec). A total of 6 file carving tools were selected for testing and are listed in Table 1. The basis for tool selection criteria included: wide file type support, advanced carving features and tool availability. Each tool listed has the associated license, tool version number and tool platform details. Additionally, the availability of tool configuration is also provided which illustrates the ability to modify the database of file signatures used by the tool.

Tool Testing Methodology

In order to produce reliable and valid results a digital forensic tool testing methodology was used which implements function orientation testing to evaluate the ability of software tools to perform specific functions or tasks [START_REF] Lyle | NIST Internal Report 7490: Digital Forensics at the National Institute of Standards and Technology[END_REF]. In this research the specific function to be tested is the ability of a file carving tool to recover assorted file types in various different scenarios. The following subsections outline the data sets, performance measurements and the testing procedure used during the experimental phase of this research.

Data Sets

Data sets in digital investigations and forensic research are usually comprised of a forensic image of a target device; for example, a bitwise copy of a computer's hard drive. However, in order to correctly evaluate file carving tools and produce reliable results, detailed knowledge of the data contained within the data set is essential. The use of documented data sets provide a baseline for scientific evaluation of tools and research reproducibility of useful findings to the academic community and practitioners alike [START_REF] Garfinkel | Bringing Science to Digital Forensics with Standardized Forensic Corpora: Digital Investigation[END_REF]. Therefore, specific purpose based data sets for testing file carving tools were used. Each data set has extensive documentation including the following details: 1) File name; 2) File type; 3) MD5 hash value; 4) File location (offset); and, if pertinent, 5) File scenario. A total of 3 data sets were used to test tool performance:

1. Basic Data Carving Test #1 (11-carve-fat.dd) 42. DFRWS2006 Forensics Challenge Data Set (dfrws-2006-challenge.img) 53. Baseline Carving Data Set (bcds.raw)(see following section) Baseline Carving Data Set: A new data set was created specifically for the second testing portion of this research. Justification for this is based on several limitations of data sets that are currently available. Firstly, the structure of files in the available data sets are not representative of, or in proportion with, data encountered in real-world investigations; for example, 11-carve-fat only contains contiguous files, while the DFRWS challenge data sets are predominantly fragmented (being designed to advance carving techniques, not test the performance capabilities of carving tools). Additionally, the variety of file types contained within the identified data sets are limited in scope.

The newly created data set was dubbed Baseline Carving Data Set 6 . The overall purpose is to represent a file structure that is indicative of what may be encountered in investigations in order to provide more viable carving performance results. It included numerous different user file types (a total of 25 different file types, and 67 files in total). Various file structures are also tested based on file sizes, fragmentation rates and gap sizes from an analysis of file systems from the wild [START_REF] Garfinkel | Carving Contiguous and Fragmented Files with Fast Object Validation: Digital Investigation[END_REF]. The file types selected were classified into 4 distinct categories:

1. Documents: DOC, XLS, PPT, DOCX, XLSX, PPTX, PDF, TXT, HTML 2. Images: JPG, PNG, GIF 3. Multimedia: MP3, WAV, MPG, AVI, WMV, WMA, MOV, MP4, FLV 4. Archive: ZIP, 7ZIP, GZIP, RAR

The following file structures are to be tested: 1) Contiguous files; 2) Fragmented files; and 3) Partial files. All documents and images used in the data set were sourced from the Digital Corpora, which provide an unrestricted file corpus7 of 1 million real files sourced from web servers in the .gov domain and come with associated file metadata [START_REF] Garfinkel | Bringing Science to Digital Forensics with Standardized Forensic Corpora: Digital Investigation[END_REF], while all multimedia and archive files were sourced from the public domain. This allows unrestricted distribution of the completed data set to other researchers or tool vendors.

Performance Measurement

The performance of file carving tools can be measured based on the ability to recover correct files from a data set while avoiding the recovery of incorrect, corrupt or partial files. A widely known performance measurement used for Information Retrieval was applied to determine the performance of each tool. The measurements include versions of Recall, Precision and Fmeasure metrics which were modified specifically for tool testing performance 8 . The following 4 quality measurement metrics with associated symbols are defined below [START_REF] Kloet | Master's Thesis: Measuring and Improving the Quality of File Carving Methods[END_REF]:

carving Recall( c R) = all -sf n -uf n all (1) supported Recall( s R) = sp -sf n sp (2)
carving P recision

( c P ) = tp tp + uf p + 1 2 kf p (3) carving F measure( c F m) = 1 α 1 c P + (1 -α) 1 c R (4)
-All (all ) refers to the total number of files in a data set.

-Supported files (sp) define the total number of file types in a data set supported by the specific carving tool. -True positive (tp) is a file that is correctly carved from the data set.

-False positive is any carved file which is not a true positive. Known false positive (kfp) are files identified by the tool output as incorrect or corrupt, while unknown false positives (ufp) are false positives not identified as incorrect by the tool. -False negative is the fraction of a file that was not correctly carved. A supported false negative (sfn) is the fraction of a file not carved by a tool, while an unsupported false negative (ufn) is a file type not supported by a tool. -Alpha (α) is the factor used to assign weight to the relative importance of recall compared to precision. For this research α = 0.5, meaning recall and precision each make up 50% of the importance of the Fmeasure metric.

The speed of processing a data set, measured in Megabits per second (Mb/s), will also be recorded to determine the time taken to perform file carving on the various selected data sets 9 . Furthermore, each test will be run 5 times to calculate an average processing speed.

Score Interpretation:

The tool quality is tested and scored with a value between 0 (low) and 1 (high). Each of the 4 performance metrics and possible reason(s) of the resultant score are reviewed below [START_REF] Kloet | Master's Thesis: Measuring and Improving the Quality of File Carving Methods[END_REF]:

1. carving Recall: Tests the ability of a tool to extract a high number of correct files from the data set. Low scores are either caused by unsupported file types, file structures or tool failure. 2. supported Recall: Similar to carving recall, but determines the ability of a tool to extract a high number of supported file types only. Low scores are indicative of tool failure to extract only supported file types. 3. carving Precision: Measures the correctness of the tool, where low scores are usually indicative of a large number of false positive files carved. 4. carving Fmeasure: The results of the recall and precision scores are combined to provide an overall score for a tool, thus enabling indicative comparisons to be made.

Testing Procedure

A rigorous testing procedure was implemented to ensure that correct data collection and analysis was achieved in order to provide accurate results. At the outset each file carving tool was sourced and the tool documentation reviewed extensively. The selected tools were then run against the 3 specified data sets and results compared to the appropriate data set documentation. The specific testing procedure used in this research is adapted from 2 previous similar studies [START_REF] Kloet | Master's Thesis: Measuring and Improving the Quality of File Carving Methods[END_REF][START_REF] Tomar | Analysis Framework for Quality Measurement of Carving Techniques[END_REF] and is made up of the following phases:

1. Determine true positives: Calculate and compare MD5 hash values for all output from the file carving tool against the MD5 hash values from the data set documentation 10 . The remaining output files are then checked to determine if the carved file occupies the same block ranges as the file in the data set. If either of the 2 scenarios are true, files are marked as tp matches. 2. Determine false negatives: A combination of piecewise hashing [START_REF] Kornblum | Identifying Almost Identical Files using Context Triggered Piecewise Hashing: Digital Investigation[END_REF] coupled with manual analysis was performed on tool output to determine any remaining false negatives and the fraction weight for files not already accounted for. 3. Determine known false positives: The log file created by each specific tool is then reviewed to identify any carved files which are marked as incorrect or corrupt. These files are marked as a kfp and counted accordingly. 4. Determine unknown false positives: The remaining output files are marked as ufp and counted accordingly. 5. Calculate performance measurements: The 4 performance metrics were then calculated using the defined formulae and the findings tabulated.

Each selected file carving tool was run against the target data sets and the testing procedure implemented. Comparison of the results were made of the first two data sets against those of a previous similar study followed by testing results from the newly authored Baseline Carving Data Set.

Results & Comparison to Previous Research

The six file carving tools were each tested against the 11-carve-fat and the DFRWS2006 data sets. Tables 2 &3 show the results as calculated from the defined performance measurements as well as the processing speed of the tool.

The results were then compared to the previous findings collected by Kloet in 2007 [20]. An arrow is displayed to indicate either an increase or a decrease in the comparative performance score of each tool11 . A high overall performance was achieved by most tools on the 11-carve-fat data set, due to wide file type support and because only contiguous file structures make up the data set. WinHex and PhotoRec produced identical results and were noted for obtaining the highest performance scores, where only one false negative carving result was counted. Interestingly, all tools failed to carve a JPEG file with a corrupt header which demonstrates the importance of a complete and uncorrupted file header to allow correct file type identification from raw data. In comparison to previous findings it was anticipated that there would be a widespread increase in tool performance. Both FTK and PhotoRec did have increased performance scores apart from the precision results from FTK which was caused by 9 false positive carved files. It was also discovered that decreases in performance were from tools with a highly editable configuration file (Scalpel & Foremost) and it is the author's opinion that a different method of tool configuration was possibly used in previous testing. This is justified by the lower recall but higher precision scores for Scalpel & Foremost. More file signatures could have been enabled during testing, but preliminary results indicated a very large number of false positives, thus, would have resulted in increased recall but decreased precision scores for each tool.

Each of the tools supported all 11 file types in this data set, therefore the carving recall and supported recall results are identical for each tool. Due to the very small size of the data set (62MB), the processing speed results are not conclusive findings of tool speed performance. Compared to previous findings all Fmeasure scores showed an increase indicating that the overall performance of file carving tools has improved for the scenarios in this data set. However, both carving recall scores were down albeit very close to previous findings. The decreases in performance may, again, be due to differences in tool configuration or operation varying between this research and the previous study. The exclusion of known bad file signatures recovering less true positive matches but also producing dramatically fewer false positive matches dictates higher precision but lower recall scores; e.g. by default Foremost has 3 file signatures for JPEG images one of which is known to produce high false positives but would have resulted in additional files recovered. Another potential reason for lower recall scores was that sector boundary scans (of 512 bytes) were specified during testing.

Baseline Carving Data Set Results

Slight changes were made to the testing procedure during testing the Baseline Carving Data Set as comparison of results to previous research was not necessary.

Firstly, carved results must validate in order to be counted as a true positive. A method known as fast object validation was implemented which attempts to open the file using it's native application without generating an error message, therefore, validating the carved file [START_REF] Garfinkel | Carving Contiguous and Fragmented Files with Fast Object Validation: Digital Investigation[END_REF]. Secondly, the performance measurement scheme was updated to include the counting of true positives as a fraction, similar to the original method of counting supported false negatives as a fraction. The reasoning was that true positive matches are commonly carved as a fraction of a file, a notable example being a thumbnail image carved from a JPEG image which displays the original image but in a smaller file size quality. Additionally, with the updated procedure, true positives, supported false negatives and unsupported false negatives should always equal the total number of files in the data set. This can be summarised as: tp + sf n + uf n = all.

The results displayed in Table 4 show the performance results of each tool for each measurement metric along with the corresponding processing speed results. Additionally, optimised testing was performed for 2 of the tools identified as Scalpel Opt and Foremost Opt. Testing of the Baseline Carving Data Set revealed that the greater variety of file types and file structures proved difficult for most file carvers to efficiently extract a high percentage of files. Nevertheless, PhotoRec and WinHex were again the top performing file carving tools. PhotoRec had a slightly higher Fmeasure score due to obtaining a higher recall score. Both carvers also supported all 25 different file types, however, WinHex had a notably higher processing speed. EnCase, FTK, Scalpel & Foremost all retained a high number of false positive files resulting in very low precision scores and in turn decreasing the overall Fmeasure result. The majority of the errors were caused by the MPEG file type, defined by short and very common header values which produced hundreds of false positive carved files. Both Scalpel & Foremost carved over 5,000 false positive MPEG files while FTK carved 300 false positive MPEG files. The low precision score by EnCase was due to carving numerous embedded files which were unable to be excluded using the embedded file hash set as most output files were corrupt. FTK, Scalpel & Foremost also carved out embedded files which were able to be excluded using the embedded file hash set.

The default file signature databases (conf files) used by Scalpel and Foremost proved to greatly decrease performance scores, especially precision and processing speed, mainly due to excessive numbers of false positive carved files. Therefore, both file signature databases were optimised in an attempt to achieve better performance results. This involved adding new file signatures for Office 2007, HTML, MP4 & FLV file types and updating existing file signatures for JPEG, PNG & Office 2003 file types. Additionally, maximum file sizes were updated and the MPEG file signature was removed from the databases. As the results indicate both Scalpel Opt & Foremost Opt had a dramatic increase in Fmeasure score from 0.007 to 0.607 and 0.008 to 0.607 respectively which demonstrates the importance of tool configuration and file signature databases used.

The use of a significantly larger data set (237MB) and complex file structure give a better understanding of the processing speed of the 6 tools. The results indicate that, as expected, processing speed decreases greatly as the number of false positives increase. This is specifically caused by the time required to write false positive file matches to permanent disk storage.

Discussion of Findings

The experiment results highlight numerous insights into the current performance of file carving tools in terms of capabilities and limitations. One of the most important factors is a detailed knowledge of tool configuration and the selection of file types, or signatures, chosen by the investigator for potential recovery; for example, MPEG and ZIP files proved difficult to carve without numerous false positives due to common header values. In this scenario manual analysis, or a specialised carver developed for a specific file format, may be implemented to enhance file recovery. However, with the increasing sizes of targets being investigated, such detailed analysis may be hindered by technical or time frame limitations.

Another important configuration option is the specification of sector size. Targeting the beginning of a sector offset for file headers greatly reduced false positive results for all tools where this option was available. However, enabling sector scanning also has the limitation of potentially missing files of interest and, as this research discovered, embedded files could not be recovered separately from the original container file.

The selection of the right tool for the job at hand is essential; for example, Scalpel uses header-based carving very efficiently with high computational performance on large data sets whereas PhotoRec uses predominantly structurebased carving with potentially lower computational performance. However, Pho-toRec results illustrated that a higher percentage of correct files was usually carved while also minimising false positives. Knowledge of specific file types and associated file structure also contributes to more efficient tool usage and improved carving results.

In terms of file structure the results reinforce that contiguous files are much simpler to carve compared to fragmented files. Nevertheless, most tools were found capable of extracting the base fragment of a high percentage of fragmented files from each data set. Again, implementation of manual analysis may then provide complete file recovery. The inability to reconstruct file fragments, despite advanced academic research and proof of concept software development, is potentially troublesome to practitioners. However, it was identified that the type of data separating fragments is an important factor in how well a carver could extract the fragmented file; for example, an HTML file intertwined with a TXT file separating the two fragments was difficult to recover whereas a JPEG document separated by randomly generated data or another JPEG proved simpler to recover.

There are numerous factors influencing the processing speed of a file carving tool and it can be highly dependant on the avoidance of carving and writing false positive files. Additionally, the file carving technique used will also affect processing speed. In general, the more complex the extraction method, the slower the processing speed. Another factor is the scan type selected on tools; for example, PhotoRec has a brute force mode scan which greatly increases scan time while Foremost & Scalpel have a quick mode which decreases scan time by only searching the start of a block of the input file as specified by the investigator.

Conclusion

In conclusion, this research investigated the performance of 6 file carving tools by conducting testing on various data sets and analysing tool output. The fact remains that there is no single best file carver. However, informed selection of the correct tool for a specific task plus knowledge of tool configuration stand out as the most important aspects to increasing both the number of files recovered and the reliability of tool output. Additionally, the findings highlight the ongoing issue and limitations of reconstructing file fragments.

A selection of available tools has also been compiled from this research to promote and advance future research. A new file carving data set, post processing file validation scripts and tool configuration files have been authored and made available for use 12 .

Future advancement of techniques and tools based on academic research could greatly improve the performance of file carving tools. Implementation of advanced data abstractions to store file carving metadata, continual advancement of file validation techniques and the automated post-processing of carving output can all help to increase file carving file performance. Additional research is also needed to reverse-engineer new file types to support the carving process. File carving, however, remains a valuable technique enabling the recovery of files and the retrieval of potential evidence for digital investigations.

Fig. 1 .

 1 Fig. 1. A simplified diagram displaying various file structures where each square represents a single storage block. A contiguous (File A), linear fragmented (File B ), nonlinear fragmented (File C ) and partial (File D) file structures are illustrated, where each block of a file is numbered consecutively (e.g. N1, N2 . . . Nn). A base-fragment, file fragment and file fragmentation points are also displayed. (Source: Figure adapted from [8] and [12])

  Although the DFRWS2006 data set contains only 6 different file types the image layout is significantly more complex than the 11-carve-fat data set. It includes 15 contiguous files and 17 fragmented files. Due to the difficulty of carving fragmented files, the scores for all tools were much lower. PhotoRec had the highest overall performance and extracted the most positive carving matches and lowest rate of false positive results. WinHex had the second highest overall Fmeasure score and the second lowest number of false positives.

Table 1 .

 1 File Carving Tools Used During Testing

	Name	License	Version Platform Configurable
	EnCase	Proprietary	7.05	Windows	No
	FTK	Proprietary	4.1	Windows	Yes
	WinHex	Proprietary	16.8	Windows	Yes
	PhotoRec Open Source	6.13	Multi	No
	Scalpel	Open Source	2.0	Multi	Yes
	Foremost Open Source	1.5.7	Linux	Yes

Table 2 .

 2 File carving performance scores for 11-carve-fat.dd

	Tool	Carving	Supported	Carving	Carving	Processing
		Recall	Recall	Precision	Fmeasure	Speed (MB/s)
	EnCase	0.669	0.772	0.500	0.572	7.750
	FTK	0.736	0.736	0.733	0.735	6.889
	WinHex	0.933	0.933	1.000	0.966	31.000
	PhotoRec 0.933	0.933	1.000	0.966	20.667
	Scalpel	0.800	0.800	0.917	0.854	10.333
	Foremost 0.708	0.708	1.000	0.829	62.000

Table 3 .

 3 File carving performance scores for dfrws-2006-challenge.img

	Tool	Carving	Supported	Carving	Carving	Processing
		Recall	Recall	Precision	Fmeasure	Speed (MB/s)
	EnCase	0.565	0.565	0.429	0.488	0.889
	FTK	0.481	0.513	0.563	0.519	1.021
	WinHex	0.623	0.623	0.622	0.623	12.000
	PhotoRec 0.813	0.813	0.963	0.881	0.980
	Scalpel	0.385	0.425	0.333	0.357	4.800
	Foremost 0.546	0.603	0.341	0.420	9.600

Table 4 .

 4 File carving performance scores for bcds.raw

	Tool	Carving	Supported	Carving	Carving	Processing
		Recall	Recall	Precision	Fmeasure	Speed (MB/s)
	EnCase	0.390	0.413	0.093	0.150	0.029
	FTK	0.445	0.508	0.098	0.160	0.714
	WinHex	0.776	0.776	1.000	0.874	21.500
	PhotoRec	0.825	0.825	0.938	0.878	3.822
	Scalpel	0.428	0.453	0.004	0.007	0.068
	Scalpel Opt	0.503	0.548	0.767	0.607	28.667
	Foremost	0.421	0.452	0.004	0.008	0.065
	Foremost Opt 0.539	0.587	0.694	0.607	24.571

http://www.dfrws.org/2006/challenge/

http://www.dfrws.org/2007/challenge/

Linear and non-linear fragmented files are also commonly referred to as sequential and non-sequential fragmentation files respectively.

The Basic Data Carving Test #1 is authored by Nick Mikus and available from: http://dftt.sourceforge.net/test11/index.html

The DFRWS2006 Forensics Challenge Data Set is authored by Brian Carrier, Eoghan Casy & Wietse Venema and avilable from: http://www.dfrws.org/2006/ challenge/index.shtml

The Baseline Carving Data Set is available from: https://github.com/ thomaslaurenson/. All documentation including data set layout, hash sets, testing scenarios and file sources is also provided.

Available from: http://domex.nps.edu/corp/files/govdocs1/

See ref.[START_REF] Kloet | Master's Thesis: Measuring and Improving the Quality of File Carving Methods[END_REF] Chapter 4 for additional information and reasoning behind the modified metrics to suit file carving performance measurement.

To ensure viable processing speed results, all testing was conducted on the same computer system with the following specifications: Intel Core i5-3570K CPU with 8GB RAM and running either Backtrack Linux 5R3 or Mircosoft Windows 7 depending on the supported platform of each file carving tool.

The Hashdeep tool (http://md5deep.sourceforge.net/) was used to first create a list of the unique hash values of all files in the data set and then to compare the MD5 hash values to the list of known files. In digital forensic investigations this process is referred to as hash set analysis.

For the 11-carve-fat.dd data set FTK, Scalpel, Foremost & PhotoRec have values to compare to previous results. For the dfrws-2006-challenge.raw data set comparative results are for FTK, Foremost & PhotoRec only.

All files are available from: https://github.com/thomaslaurenson/


W J Caelli
email: w.caelli@iisec.com.au

L F Kwok
email: cslfkwok@cityu.edu.hk

D Longley
email: d.longley@iisec.com.au

Evolving A Secure Internet

Keywords: Secure Internet, trust relationship model, Internet trust relationships

Internet insecurity is inevitable if a high proportion of Internet users are insufficiently aware of the inherent risks involved, whilst those cognizant of those risks are denied the facilities to manage and control them. This paper highlights the first issue and discusses a potential approach to the second.

Introduction

Forty years ago Scott Graham and Peter Denning [START_REF] Graham | Protection Principles and Practice[END_REF] wrote:

On the basis of the foregoing argument, we conclude that the protection system is correct and will operate exactly as intended among trustworthy subjects. Untrustworthy subjects cannot be dealt with completely by mechanisms of the protection system. External regulation, together with a system for detecting and reporting violations, is required.

Forty years later this advice is relevant because it emphasises the key role of preexisting trust relationships within information security. The focus of information security has evolved from government mainframes, to corporate information processing systems, small business and home computing and now the Internet and mobile devices. These developments involved major corresponding changes in the host environment trust relationships.

When information security developed as a topic in its own right, and as a profession, there was a natural tendency to concentrate on common themes of information security systems, perhaps at the expense of the fundamental role of preexisting trust relationships in the host environment.

In the 1980's it was commonly assumed that the global communication offered by the Internet would facilitate social cohesion; but now it would appear that the Internet can produce some damaging impacts upon society. If the current impacts have been caused by petty criminals, one could well fear the potential future impacts from organised crime or a rogue government; hence the current widespread concerns for cyber insecurity, coupled with calls for greater regulation, sophisticated defence systems and even hints of assured mutual disruption.

The host environment of the Internet comprises that of the 2 billion Internet users. Whilst the Internet itself, may be viewed from a network security viewpoint, Internet security must be directed at the trust network of the host global user society. When governments are faced with some of the social evils arising from the Internet, e.g. cyber bullying, network security techniques alone offer no solution.

Taking a broad brush approach to Internet security we could recognise that the pre-Internet society had, over millennia, evolved a remarkably successful social trust network, bonding a set of highly complex social systems. The Internet, as a computer network, certainly offers an opportunity of increasing social cohesion. Taking the lead from Graham and Denning it seems clear that the role of Internet security should be defined in terms of enhancing the effectiveness of that trust network.

This paper seeks to explore the approach based upon the concept of the Internet as communication system designed to enhance a highly evolved social trust relationship infrastructure. It suggests that a better understanding of the role and functions of existing social trust relationships could lead to the evolution of a secure sub-Internet, expanding and gradually replacing the current anarchic Internet

The paper first describes an informal personal trust relationship model, and then reviews the current state of Internet trust relationships from a user -supplier viewpoint. Finally there is a discussion on the evolution of a secure Internet service complementing the trust relationships in traditional personal activities: banking, information retrieval, social networking, entertainment etc.

Personal Trust

Overview

The role of trust in society has been widely discussed [START_REF] Fukuyama | Trust: The Social Virtues and the Creation of Prosperity[END_REF]. The term trust has such emotive affiliations that for the purposes of this paper a pragmatic definition will be adopted:

An entity trusts another entity if it is confident that it can predict the behaviour of that entity in a specified context.

Example: a householder predicts that the plumber will successfully repair a dripping tap.

Trust relationships are formed in the cot; trust relationship training and experiential learning continues throughout a lifetime. Society successfully evolved from small hunting parties, through tribal societies, agricultural communities, the industrial revolution, to the pre-Internet trust relationships, because increasingly complex societies were rendered viable by a vast trust relationship infrastructure.

One of the consequences of this infrastructure was that individuals exploited trust relationships instinctively and became less conscious of their existence. Hence a late nineteenth worker in a small village was probably more acutely aware of the importance of such personal trust relationships than a teenager in the Internet era. This apparent current lack of awareness had significant consequences in the explosive growth of the Internet.

Example: compare the attitude of a nineteenth century village child to a stranger, as compared with that of a modern teenager in a bulletin board session.

A trust relationship model is defined below and is used in a discussion on the role of such relationships on the Internet.

Trust Relationship Model

Overview. l Context -the total set of potential actions requested from the Activator; l Initiator -the party that establishes the trust relationship and subsequently sends transaction requests to the Activator; l Activator -the party that performs the requested transactions; l Security Attribute -details of the Activators ability and previous performance in performing the transactions; l Trust Level -the Initiators' estimate of the probability that requested transactions will be successfully completed by the Activator.

In general the Activator predicts that the Initiator will provide some recompense for the completion of individual transactions. Hence most trust relationships are bilateral: party A predicts that party B will satisfactorily perform the transaction, whilst party B predicts that party A will pay the bill. Hence each party plays the Initiator role, in one of the constituent relationships, and the Activator role in the other. Forming a Trust Relationship. The Initiator evaluates the Activator via the security attribute (see Fig. 1) and estimates the trust level associated that security attribute. The Activator will also set a risk profile and conduct a risk analysis; estimating the impact value of a failed transaction and estimating the risk from the impact value and trust level. If this risk is within the boundaries of the risk profile, the Initiator will propose the formation of the trust relationship with the Activator, who will usually undertake a similar process for the second half of a bilateral relationship, and accept or reject the offer.

Zero Trust Relationship.

A multitude of transactions are conducted outside the trust relationship model described above, every day such one-off zero trust relationships are employed when the potential impact is low, or the risk of not requesting the transaction is high. One common example of the zero trust relationship arises when one requests directions from a stranger. Such one-off zero trust relationships are based upon the assumptions:

l The net benefit from a large number of such relationships justifies their usage; l There would appear to be no benefit to a malicious activator; l The initiator has some limited basis, e.g. activator's appearance, demeanour to assume a beneficial outcome.

Surfing the Web provides an example of the common usage of zero trust relationships.

Transitive Trust. The difficulties associated with the task of identifying and evaluating activators is commonly bypassed with transitive trust relationships, e.g. recommendations from a trusted friend.

In a unilateral transitive trust relationship A trusts C and C trusts B, which can lead to a transitive trust relationship: A trusts B (See The trust level between A and B can be no higher than the minimum of the A-C and C-B trust levels. If transitive chains are extended then trust levels between the initiators and activators and the ends of the chain could well fall below acceptable levels for even moderate impact transactions.

Transitive trust chains may become quite long and it is essential that they commence with a non-transitive trust relationship. This condition is significant for Internet users where transitive trust is commonly employed, because, as discussed below, there are extreme difficulties in forming non-transitive trust relationships on the Internet. Appeal Systems. In bilateral relationships both parties experience a degree of risk with each individual transaction. An appeal system, trusted by both parties, can reassure them that any disputes may be resolved impartially. In effect the existence of the appeal system may be a component of each party's security attributes, effectively increasing each party's trust level.

Appeal systems may play an important role in transitive chains, counteracting the inevitable decline of trust levels along long chains; provided, of course, that the transitive chain does not extend outside the realm of an appeal system common to both parties.

Internet Trust Relationships

Overview

At the end of the 20th Century the Internet was viewed as a large computer network amenable to conventional network security. Today the Internet has evolved into a novel worldwide distributed social entity with a strong antipathy to security and regulation.

The past two decades have seen a worldwide migration of traditional activities to the Internet. Many of these traditional activities relied upon trust relationships evolved over centuries, and this paper discusses the issues surrounding the establishment of corresponding trust relationships on the Internet.

The establishment of trust relationships in a small community was facilitated by propinquity and multichannel communication, i.e. a few people in close proximity who using one or more their five senses in their interactions. The Internet user population, on the other hand, represents of the order of 30% of the world population, and a major part of its traffic is restricted to the exchange of text and graphics. This environment seriously complicates the establishment of trust relationships as discussed below.

Establishing an Internet Trust Relationship

Activator Identification and Evaluation. Initially the initiator must locate and identify a potential activator; the initiator must then select a set of activator attributes rendering that individual unique amongst the population known to the initiator, so that the initiator will be able to identify the activator when requesting future transactions.

If the initiator and activator live in a small community then the activator's physical appearance will suffice. However, as activators are selected from increasingly large populations the number of personal attributes required for unique identification grows rapidly.

The unique identification of the activator becomes even more problematic as information is collected to determine the activator's qualifications relevant to the context of the proposed trust relationship. Again such evaluation in respect of a local plumber in a small community is straightforward, but becomes increasingly problematic when such information must be collected from a variety remote sources and the initiator must verify that the activator identifying information, provided by each source, corresponds only the selected activator.

The initiator must aim at the collection of sufficient information, about the activator's potential performance in the relationship context, to estimate a trust level for the proposed relationship. Then a decision is made on whether or not that trust level is consistent with the initiator's risk profile.

Having collected the security attribute information, either directly from the activator or one or more other sources, a chicken-egg problem becomes apparent. How does the initiator verify the integrity of the information collected over the Internet? If the initiator has a trusted source of security attribute information, how was the trust relationship formed with that source? A similar problem arises if the initiator bypasses the identification and evaluation process with a transitive trust relationship. Hence it is apparent that trust relationships can only be formed on the Internet after some root trust relationship has been formed outside the Internet.

When the initiator has selected a specific activator then the initiator's problem of ensuring that future transactions are initiated with the correct activator must be addressed. Since the communication is via the Internet, the initiator and activator need to agree upon some effective authentication process for future communications. If the relationship is non-transitive root then this exchange of authentication details, e.g. public key certificates, should also be undertaken securely outside the Internet.

Authentication processes employed in communication channels assume that the communicating parties do not deliberately provide masquerading entities with the authentication parameters. Hence such authentication processes should be backed by some regulatory authority such that an individual would be held legally responsible for actions undertaken in any such masquerades.

Once the root trust relationship has been formed the Internet is, from an information security viewpoint, merely a computer network and the security facilities offered by public key cryptography may be deployed.

It would appear from the above discussion that the combination of trust relationships, formed in the traditional manner outside the Internet, may be used to provide secure roots for Internet transitive trust relationships and even trust relationship chains, thus combining the best of both worlds. This approach requires both a reconsideration of current approaches to Internet security, and a secure deployment of public key cryptography.

4

A Secure Internet Service

Overview

The period preceding the Internet experienced amazing technological advances in electronics and communications; these advances resulted in qualitative and quantitative changes; mass production of microelectronic devices provided mass access to computing and communication services. In the early years of computing developments Governments largely drove the agenda, but the Internet advances mainly resulted from market forces exploiting low cost consumer electronics. Such market forces tended to view security as a costly obstacle and the consumer was provided with a choice in many aspects of the Internet, except the level of personal security.

In conventional trust relationships the user weighs the advantages of undertaking transactions on the balance of potential gain and risk; the risk itself is measured in terms of impact probability and value. Over the past two decades it has become clear that a significant proportion of Internet users lack the detailed knowledge of Internet technology to evaluate their risks, e.g. they are unaware of potential unfavourable outcomes and associated impacts. For example: malicious code downloads, monitoring of users' Web usage, penalties of intellectual properties transgressions, lack of privacy etc.

Moreover a high proportion of Internet usage, i.e. surfing the Web, comprises apparently one off zero trust transactions (See Zero Trust Relationship in 2.2). Asking a stranger for directions is considered relatively safe because for any such single transaction the wrong information has limited impact, and the stranger is unlikely to benefit from deliberately malicious behaviour. Web surfing, however, may not fit this pattern, e.g. l a malicious posted set of false information will impact upon multiple Internet users; l monitoring of user Web actions may in some circumstances have significant long term impacts on specific users.

In recent years many users have been virtually compelled to employ Internet services because the off-line alternatives are not locally available or are too expensive. At the same time the average Internet user is provided with few opportunities to protect themselves apart from subscribing to anti-virus services and avoiding obvious pitfalls with passwords. It is proposed here that Internet users should be provided with the option of a security policy providing similar levels of security to that offered by traditional off line trust relationships, e.g. manual banking compared with current Internet banking. The proposed secure Internet service is intended to complement, rather than replace, current Internet services, and could therefore commence with a few applications allowing user demand for security to determine its success.

Internet applications may be broadly listed in two categories: text/graphics and audio-visual. The text-graphics type Internet applications consist of financial services, commercial services, information retrieval, social networking and email, and interactive education; whereas audio-visual type Internet applications include music, movies and education presentation. The following sub-sections discuss the trust relationships of these Internet applications.

Text -Graphics Trust Relationships

Financial Services. These applications normally involve a pre-existing off-line trust relationship between the financial institution and the Internet user, and could be offered with a high level of user security. The client and financial institution are in a position to exchange mutual authentication data off-line and the Internet user security then depends upon the technology employed for the authentication process (See 4.4 PKI and Secure Interface Devices) , and the security of the institutional computers.

Commercial Services. Most on-line shoppers have no pre-existing trust relationship with the Internet supplier, and few Internet users would be in a position, or prepared, to establish such relationships with individual Internet suppliers. In this case transitive trust relationships are the only option for the secure Internet service, which implies some organisation, termed here root organization, is prepared to provide a root trust relationship for Internet users (See Transitive Trust in 2.2). Consumer Protection Authorities, for example, would be well placed for such a root organization role. Such agencies not only have some role with suppliers in specific geographic areas, they often have regulatory powers and access to some appeals system. In the proposed scheme the suppliers would register with the root organization, and supply authentication data, off line. The Internet user would also register with this root organization offline and collect its authentication data. Having located a supplier on-line, and checked that it is registered with the root organisation, the user collects the supplier authentication data established with the root organization, and initiates the transaction with that supplier. The user supplier trust relationships could also be in a bilateral form, in which case the user would supply authentication data at time of registration with the root organization.

The obvious objection to this proposed scheme lies in the limited range of suppliers associated with a particular root organization; implying that Internet users would be restricted to a few suppliers, according to user's ability to register off line with various root organizations. If, however, diverse root organizations are prepared to offer reciprocal regulatory protection then they may merge off-line and provide their registered users with high trust level relationships over a much larger range of suppliers. One of the major advantages of the proposed scheme lies in the regulatory powers of the root organisation increasing the trust level of the user -supplier relationship.

The success of such a proposal is dependent upon market forces but it has the advantage that such a scheme could evolve from a small base. Information Retrieval. Information retrieval probably represents the most important single application on the Internet. Search engines provide access to a host of relevant information. Web surfing is commonly regarded as a low risk activity, although the associated privacy risk to users is underplayed. However, users are on occasions concerned about the authenticity of accessed information; if one considers print based information retrieval it is apparent that the users on such occasions are strongly influenced by the provenance of written text ranging from newspapers, legal documents to respected text or reference books.

The risk associated with Internet information retrieval was apparent in Australia when an environmental activist, armed only a mobile phone and laptop, produced a fake Internet press report causing a sharp fall in the stock market value of a mining company. Medical and health warning information is now commonly accessed over the Internet by medical practitioners and the general public; one hesitates to list the potential dangers of this situation.

In traditional information retrieval the user can easily distinguish between a leaflet, a respected newspaper or reference book in the library, whereas URLs provide only limited guarantees of provenance and even these are commonly ignored. Even if users access a reputable site, they can be seriously misled by malicious hacker alterations in the text.

In the proposed scheme a reputable publisher acts as a root organisation (see Commercial Services in 4.2) for various Web publishers, although such a root organisation would normally have limited, if any, regulatory powers. The user obtains the Web publisher authentication data from the root organisation and checks a digital signature included in the Web page, thus providing assurance on the source and integrity of the displayed text.

Social Networking and Email. Social Networking did not feature in the early security vulnerable areas of the Internet, but the current level of cyber bullying is now a topic of government concern. Faced with the Pandora's Box opened by youthful entrepreneurs one can only compare the dangers faced by teenage parents in the pre-Internet days with their woe-begotten current counterparts.

Most parents traditionally adopted individual and group strategies in relationship to their off springs' companions. At an individual level the identity, security attribute and trust level of the candidate activator were routinely assessed, because this information was available. At the group level the culture surrounding clubs for various age groups and interests highlights the interesting trust relationships between club members and the organising committee. The members trusted the local committee to vet potential members and effectively used that trust in the formation of transitive trust relationships between current and new members. Is it conceivable that a similar approach could be used to form high trust transitive social trust networks on the Internet?

Email security is particularly interesting in the context of this paper because PGP (pretty good privacy) [START_REF] Zimmermann | The Official PGP User's Manual[END_REF] addressed email security concerns and used both public key cryptography, and transitive trust for the development of a certificate chain. Email addresses can be masqueraded and from time to time one receives emails with a colleagues email address but with associated text clearly derived from another source. There are good arguments for more use of PKI in emails, particularly in large organisations, where sender certificates could include attributes informing the recipient of the role and authority of the sender within the company.

The fundamental risks associated with emails arise, however, from the curse of immediacy. In the pre-Internet era many people re-read their outgoing correspondence before sealing the envelope, reflecting on the contents and potential reactions of the recipients.

Interactive Education. If the Internet is to have an increasing role within education, in particular higher education, the risks associated with online tutorials and assessment deserve detailed consideration. The potential pitfalls, and associated litigation, arising from tutor -student interactions and assessment decisions suggest that a serious re-consideration of academic trust relationships, and their implementation in a global Internet based educational network, would be advisable.

Audi-visual Trust Relationships

Overview. Originally Internet security was based upon conventional network security dealing with primarily with textual data. One of the perhaps more surprising outcomes of enhancing a single sense channel (sight) with a second channel (sound) is that two teenagers with Web cams can now securely mutually authenticate over the Internet without the aid of cryptography.

Audio visual applications have at least two significant security implications: intellectual property and privacy. Governments have been concerned both with protection with corporate profits and the impacts of cyber bullying, responding with strict legislation for the one, and serious hand wringing for the other.

Intellectual Property. The trust relationships associated with theatres and cinemas normally took the form that the client predicted the quality of entertainment provided would be compatible with the price of the entrance ticket, the supplier predicted that the audience would not express significant disapproval during or after the performance. Such trust relationships are significantly different when the client plays back some digitised music or video. The supplier now takes the risk of loss of income from piracy of the digitised information, whilst playing back such digitised information make involve the risk of penalties for intellectual property legislation transgressions.

In a previous generation the music industry employed technology that made illegal copying expensive; the publisher bore the cost of producing vinyl disks and the consumer purchased a hi-fi system capable of playing, but not reproducing, that disk. Digitisation revolutionised this industry, the supplier was no longer burdened with the cost and distribution of the disks, and the consumer purchased equipment capable of both play and reproduction. The downside from the supplier's viewpoint was the potential theft of their intellectual property. Their solution is to pass the responsibility of the protection of their intellectual property to the user, with major financial penalties for transgression; at least some governments have actively supported this initiative. An alternative solution to the intellectual property dilemma involves a reversion to the previous situation in which the supplier product was supplied in a form that could be played but not cheaply reproduced.

Cryptography combined with a special purpose secure playback devices could provide such a solution. In effect, the encrypted digitised data supplied could only be decrypted and played in the secure device holding a private key technologically protected against illegal access.

Privacy. There are no current technological solutions to the age old problem of the presumed friend who maliciously passes on intimate secrets. Social networking has unfortunately provided an international broadcast audio visual system for such indiscretions. As such it has exemplified the problems of the Internet world lacking effective social trust relationships. In previous generations teenagers were at least inculcated into the imperfect world of personal trust relationships (see Social Networking and Email in 4.2).

PKI And Secure Interface Devices

PKI. An Internet-wide PKI would provide a parent-child hierarchy of Certificate Authorities and presumably unique identification for each user. However such a system could pose a significantly enhanced threat of identity theft since it would rely upon the cryptographic strength of a particular public key algorithm, and the integrity of a vast host of employees charged with issuing certificates as well as the underlying computer systems used to create, store and distribute the base certificates themselves.

The proposed Internet trust relationship networks with root organizations uses a local PKI, and extends it with sibling certificates issued by the root organizations to their trusted individual Internet suppliers and, if appropriate, to their registered users. The user, and supplier, offline registration process with the root organization would thus involve face to face authentication and exchange of certificates.

Secure Interface Devices. The theme of this paper is that an Internet user should have the opportunity to benefit from trust relationships similar to that enjoyed in the pre-Internet era. Exploiting the proposed Internet transitive trust relationship network requires: l secure end to end authentication; l security of communication channels; l some means of estimating trust levels over transitive chains, which may extend beyond the aegis of local appeal systems.

PKI Certificates exchanged between activators and initiators can facilitate unilateral or bilateral mutual authentication, and the exchange of cryptographically secured messages. The advantage of this proposed system is that it can mimic the conventional trust relationships practised outside the Internet where users make value judgements on transactions based upon impact and trust levels.

The user private key in this arrangement is the keystone to user security; its value and processing must be protected from the malicious code inevitably residing in the user's computer. Current technology has produced a plethora of handheld smart devices and hence a cost effective secure interface device capable of protecting cryptographic private keys and public key certificates can be reasonably postulated.

In keeping with the principle that the Internet trust relationships are either established outside the Internet or via transitive trust chains, certificates for nontransitive trust relationships, e.g. Internet banking, and root transitive trust servers would be loaded directly into the secure device.

The secure device has the task of extracting and checking certificates and supplier public keys derived from certificates, including sibling certificate chains, aided by attributes of the various certificates, and performing the corresponding cryptographic operations.

The sibling certificates may also be employed to facilitate end to end trust levels in long transitive chains. Attributes of these certificates may contain details of link trust levels and existence/ non-existence of end to end appeal facilities. Given some monetary impact value for the transaction the secure device could even provide warnings of risky transactions.

Conclusions

The user's security role is perhaps the most significant issue arising from this paper. In conventional information security environments, similar to those addressed by Scott Graham and Denning [START_REF] Graham | Protection Principles and Practice[END_REF], the host organization information security system was designed to strengthen the pre-existing organisational trust framework. To this extent the user had a somewhat passive security role, e.g. protection of passwords etc. With Internet security, however, there is no host organization and the users have a major security role, including responsibility for their own risk analysis and management. Unfortunately the average user is neither equipped to fulfil this role, nor in a position to establish a requisite level of security. It is therefore of some concern when suggestions are made that users should be held liable for security breaches, e.g. penalties for harbouring botnets.

This paper emphasises the key role of users in Internet security and highlights two major factors of that role: user Internet security education, and facilities for the deployment of trust relationships with trust levels consistent with user risk. Such a user education requirement is not particularly novel; vehicle drivers are not legally permitted to use public highways with skills limited to manipulation of automobile controls, and total ignorance of road traffic interactions. The current Internet user security awareness situation may perhaps be traced to an ill-informed replacement of traditional IT education with minimalist mouse icon click training, and should be redressed as a matter of urgency.

The, hopefully increasing, proportion of Internet users with sufficient knowledge and skills to protect themselves will be the key drivers, and only hope, of a future adequately secure Internet. This paper discusses the harnessing of traditional trust relationship skills, and the facilities required to implement secure Internet trust relationships. The fundamental problem of establishing secure Internet trust relationships is addressed with a proposal for transitive trust relationships, supported with secure authentication, rooted on traditional trust relationships formed off line

  Fig 1 illustrates the Trust Relationship Model. The model parameters are:

Fig. 1 .

 1 Fig. 1. Trust Relationship Model: The Initiator predicts that within the context of the trust relationship the Activator will behave as predicted with a probability equal to the Trust Level value; the Trust Level is a function of the Activators Security Attribute,

  Fig 2). Corresponding bilateral transitive trust relationship Transitive trust can take one of three forms: l Introduction: C merely passes B's identifier to A. l Recommendation: A's trust level in B is influenced by C. l Delegation: B is merely a component in the performance of the tasks; the trust level assigned by A in the A trusts B relationship, is equal to that of A's trust level with C, e.g. B is an employee in Bank C.

Fig. 2 .

 2 Fig. 2. Transitive Trust: A trusts C, C trusts B, A has a transitive trust relationship with B. A recommendation transitive trust is commonly employed when C is in a better position to evaluate B's security attribute than A, and in general A should have a high trust level in C; such transitive trust levels are highly conditional, e.g. l The context of A's trust in B must be a subset of the context C's trust in B; l If there are a large number of C's trusting a unique B then an average of these trust levels may be appropriate in the estimation of the transitive trust relationship; l There should be no significant time gap between the last transaction of the C trusts B relationship and the first transaction of the A trusts B relationship. l C's identifier for B must be unique in the union of population sets known to A and C.