Slobodan Lukovic
email: slobodan.lukovic@usi.ch

Igor Kaitovic
email: igor.kaitovic@usi.ch

Systems Engineering for Assessment of Virtual Power System Implementations

Keywords: systems engineering, modeling, SysML, VPS, assessment

In this work we present an adoption of systems engineering methodology for design and assessment of a Virtual Power System (VPS). The VPS has been defined as an aggregation of distributed energy resources, consumers and storages which can operate autonomously, and is presented to the power system as a single unit in technical and commercial terms. The complexity of these critical systems is tackled by means of systems engineering. We have applied our approach in scope of a research project AlpEnergy.

Introduction and Background

In the present work based on achieved results in the course of the international Al-pEnergy project we provide description of a methodology used for design, implementation and assessment of Virtual Power System (VPS). VPS integrates, manages and controls distributed energy generators, electrical vehicles (and other controllable loads) and storage capacities and links their technical operation to the demand of consumers and the energy market. Detailed VPS description providing basic definitions and explanation of the concept is presented in [START_REF] White | [END_REF][START_REF] Lukovic | Virtual Power Plant as a bridge between Distributed Energy Resources and Smart Grid[END_REF]. One of the main challenges of the project is considered to be tackling of multidisciplinary nature of VPS concept and developing of a model of the supporting ICT structures which are crucial to critical infrastructures. Moreover, an evaluation strategy for pilot implementations was supposed to be developed. To cope with the challenge we have adopted systems engineering methodology already proven as a very efficient instrument to tackle complexity of different heterogeneous systems and different technical backgrounds of stakeholders [START_REF] Weilkiens | Systems Engineering with SysML/UML: Modeling, Analysis, Design[END_REF]. The methodology is based on instruments provided by SysML modeling language -widely accepted UML profile for modeling of complex heterogeneous systems. The methodology is presented in details in [START_REF] Lukovic | Adopting system engineering methodology to Virtual Power Systems design flow[END_REF], [START_REF] Kaitovic | Adoption of Model-Driven methodology to aggregations design in Smart Grid[END_REF] while similar approach is also applied in [3]. In this work we focus on assessment of different project implementations showing how proposed methodology can be used for that purpose.

VPS concept supposes a flexible structure that embraces widest set of technical and commercial issues. Furthermore, VPS model has to absorb all the changes and adaptations in the system and its environment and for that reason has to be constantly updated depending on the newly identified stakeholders or requirements as well as results obtained from results provided by pilot implementations.

VPS design, involves many stakeholders that are not ICT (Information and Communication Technologies) experts. For that reason it was necessary to propose a rather simple, easy to explain -communication and system design strategy. Therefore, we adopted systems engineering methodology, still capable of coping with dynamic model changes [START_REF] Kaitovic | Adoption of Model-Driven methodology to aggregations design in Smart Grid[END_REF]. Moreover, the same methodology has to take into account particularities of project and be able to embrace various VPS requirements, results and particularities of implementations from different partners. The main benefit the methodology brings is that it supposes an interactive and not a straight-forward process of system design and that is fully open to changes and upgrades that are inevitable in project development. The ultimate result of the methodology application to the VPS is a reference architecture that is later used for assessment of specific implementations.

General Approaches and methodologies

The first step of the methodology represents context description. It refers to unambiguous definition of system environment in terms of surrounding systems and their relations to the designed system. By correlating information from relevant research projects [START_REF]E-ENergy project[END_REF][3][START_REF]ADDRESS project[END_REF][START_REF]SmartGrids Technology Platform[END_REF] we managed to identify existing and foreseen future stakeholders as well as system context in terms of surrounding systems as well as VPS itself.

A full set of identified stakeholders, includes individuals and organizations: Distribution System Operator (DSO), Electricity retailers, Energy Exchange Stock, Energy market legislation, Local authorities, Equipment producers, VPS shareholders, consumers (i.e. Residential users, Industrial users etc.),as detailed in [START_REF] Kaitovic | Adoption of Model-Driven methodology to aggregations design in Smart Grid[END_REF]. Still, as already stated, additional stakeholders could emerge in the future. Moreover, some of the stakeholders identified above are foreseen to just appear or to drastically change in the future (e.g. Energy Exchange Stock). Such changes would consequently trigger additional changes in system requirements and models proposed.

Requirements engineering that includes collecting, tracing, analyzing, qualifying and managing user requirements constitutes the next stage of the system design. The main purpose of this phase is the efficient extraction of system requirements and their refinement trough use cases that are latter traced to specific components.

For each user requirement collected from stakeholders (or in particular case from some of the project partners), a set of system requirements has been derived. The same set of system requirements has been mapped to use cases describing system functionalities and services that are finally traced to one or a group of system components [START_REF] Kaitovic | Adoption of Model-Driven methodology to aggregations design in Smart Grid[END_REF]. A conceptual (i.e. general abstract) system model of VPS is supposed to serve as an intermediate step for better orientation in development of reference model (as shown in [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF]). The next step represents behavioral modeling of each system functionality presented through use cases and assumed set of components [START_REF]ADDRESS project[END_REF]. Interaction based behavioral models are presented by means of sequence diagrams. While progressing with behavioral models of system functionalities, system structure changes in terms of inserting additional components or changing their roles. In some cases, struc-tural change will induce additional behavioral changes. The outcome of this step is set of consistent structural and behavioral models. It is important to notice that these of models are developed in parallel and they impact and complement each other. Based on these models methodology finally yields reference model.

Being flexible and iterative, methodology described can be used in different stages of project development. That makes it suitable for the application to the research projects such as VPS design is. Since not all stakeholders are known at the moment (e.g. energy market), some requirements are tailored to project goals and realistic assumptions.

VPS requirements and use cases definition

Having stakeholders identified, requirements engineering phase starts by collecting user requirements from them. Once initial set of user requirements has been obtained, initial abstract model of the system has to be defined. This refers to identification of components, so that system requirements related with components and their interaction can be identified. For each user requirement separate sequence diagram has been developed representing the way that requirement can be satisfied through interaction of initially assumed VPS system components and surrounding systems. While focusing on functional ones, we have carefully collected and organized user requirements in three packages representing communication, commercial and technical requirements. For each interaction that appear among VPS and surrounding systems as well as so far identified internal components, system requirement is defined. Each user requirement has been mapped to one or more use cases describing VPS functionalities (as detailed in [START_REF] Kaitovic | Adoption of Model-Driven methodology to aggregations design in Smart Grid[END_REF]). As the system modeling progress, set of system components could change, and those sequence diagrams could be re-engineered after validation.

Applying the same principle to all other user requirements, the final set of system requirements has been derived. In fact, user requirements are mapped into system ones. The definition of use cases initiates behavioral modeling of the system. Use cases development is based on system requirements, through grouping and refinement process. A few basic use cases, describing the main functionalities of the VPS are defined at first and related with the actors and internal components involved in operations they describe. While defining those main use cases relating them with actors, major user requirements were taken into account (as shown in [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF]). This marks the starting point for understanding the system functionalities. Each stakeholder can identify use cases that he is interested in, and latter follow decomposition only of these use cases, unburden from the functionalities of the rest of the system. So, managing system complexity is done through its functional and hierarchical decomposition.

Use-cases decomposition

Each of the major use cases is further decomposed through more fain-grained diagrams with atomic use cases directly traced (i.e. related) to system requirements. Still, further extension of all diagrams is possible and even expected with project evolution as new requirements could evolve. The model represents a result of an iterative process taking place during entire course of the project. As an demonstrator of the further steps of the methodology we focus on energy trading scenario (i.e. use case) which implies external and internal contracting. In later steps these use cases will be elaborated in details. Use cases are related by proper requirements as shown in the figure .  Applying a comprehensive approach based on initial findings on system functionalities and composition (coming from related projects and knowledge of the project partners) a general abstract model of the VPS has been developed as an intermediate modeling result (see [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF]). It defines initial set of components and their interactions and serves for orientation in further phases of the modeling methodology.

Basic system components

Brief description of the main components in the model is given in the following:  Control Center are manages the system assuring the power quality.  Advanced Measuring Infrastructure (AMI) goes way beyond consumption metering and includes measuring of additional parameters and their collecting  Actuating Embedded Systems (AES) are extending the SCADA functionalities and directly control field devices (smart load, DER or storage).  Trading Agent is envisioned as component that handles all the commercial issues of the VPS including biding, energy selling etc.  VPS operation manager is the brain of the system that manages energy balance, verifies the feasibility of predicted production, etc. Different kinds of scenarios (i.e. use cases) have been developed. In order to show effectiveness of the approach, we use an example of energy trading. Energy trading for AlpEnergy VPS considers 'day-ahead' market contracting and it may concern amount and prices of bulk energy, ancillary services and so forth. This major use case has been decomposed in two phases (i.e. sub-cases): External contracting-negotiation between SmartGrid; Internal contracting -negotiation -between VPS and its clients. We will show main actors and describe their interaction in the following.

External and internal trade contracting

Basically the process starts by a request from the VPS manager (which keeps portfolio with preferences and statistics of all VPS consumers and producers) to the Smart Grid for obtaining the energy price. The trading agent of VPS communicates with the AMI and the predictions manager for current meter data and energy balance predictions, respectively, in order to verify affordability of the contract (e.g. offered price and amount of energy) obtained from the Smart Grid. Eventually, negotiation takes place between the VPS manager and Smart Grid and the process iterates until an optimal price is reached. The sequence diagram describing this process is given in Fig. 1. Ones the contract is set at the level of entire VPS it is also necessary to negotiate in the context of local contracts (for each VPS member in particular). In this case VPS manager requests from the tariff manager to calculate the dynamic prices for each individual consumer (or producer). AMI and predictions manager are contacted again to check current and expected energy balance in the system and per each VPS member. Demand Side Management (DSM) is involved to customize offers for each VPS member individually based on their statistics and portfolios. The price is then negotiated with the local energy manage (LEM -which is a component assigned to each member of VPS), since the price in this case is a local (i.e. internal VPS matter), rather than external. The sequence diagram in Fig. 1 (on the right) describes the process. Applying the methodology, we continue with defining system behavior and structure needed for achieving each of the use cases previously defined. For each VPS functionalities/use case a specific sequence diagram has been derived describing how particular use case can be satisfied through interaction of various components. Initially each component has some predefined set of functionalities that is being extended and additionally defined through each sequence diagram. Basics of behavioral model of the system are set in the previous Section where sequence diagrams were given (Fig. 4 and5) denoting information flow.

Starting from the general abstract model defined as a tentative system structure at early phase of the project and iteratively improving it through new findings from developed use cases we build a set of main VPS components together with identified functionalities.

Eventually we present simplified VPS internal block diagram providing details about information flow between components which facilitates defining the communication standard inside VPS. With a clear identification of components and it's functionalities, same methodology described here can be used for deriving further finegrain model of the components. It should be noted that model presented is derived from the requirements of AlpEnergy project while considering contemporary results of other relevant projects as well [START_REF]E-ENergy project[END_REF][3][START_REF]ADDRESS project[END_REF]. Thus, with additional upgrades, it can be used as a reference point for other similar projects dealing with Smart Grid aggregations.

4.1

Building reference model

General, abstract model of proposed ICT supporting structure for VPS (given in [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF]) has been developed according to existing state-of-the-art solutions and inputs coming from different pilot implementations. The model is a result of discussions among all the partners and wide compromise about all its elements has been achieved. The later findings obtained through described systems engineering process have resulted in VPS structural models. As a very next step in the project a reference model of VPS ICT structure has been built. It is used as a central point of the AlpEnergy project and it is considered to be one of its main achievements as it elaborates the result of mutual efforts and gives an overview on the system infrastructure.

The reference model shown in Fig. 1 is intended to be a starting point for ICT assessment process. It represents a suggested solution that would also serve as a reference for evaluation of all pilot implementations. Apart of that, as a visual description, it can assist project dissemination activities as it has been made to be general, comprehensive and understandable using the widely accepted SysML modeling language.

The reference model has been adopted to identified specific requirements of Al-pEnergy and regularly upgraded according to proven solutions coming from exact pilot implementations. As lighthouse guidelines for abstract model we have considered solutions provided by related relevant international projects like [START_REF]E-ENergy project[END_REF][3][START_REF]ADDRESS project[END_REF], respectable international institutions and initiatives [START_REF]SmartGrids Technology Platform[END_REF] and also cutting-edge research achievements [START_REF] Li | Smart Transmission Grid: Vision and Framework[END_REF][START_REF] Sauter | End-to-End Communication Architecture for Smart Grids[END_REF]. The basic abstract model developed from such a theoretical approach is developed in SysML modeling language, it represents an intermediate step.

Still such a model served just for orientation and provided good guidelines for other phases of the project development. The input from existing pilot implementations and experiences gained in field testing are another precious source of information needed for development of the precise reference model. We interviewed Al-pEnergy implementing partners and studied their technical documentation. Nevertheless, without an unified describing method and in absence of defined mutual understanding platform for VPS design we faced many problems in extracting technical details from available informal descriptions.

System composition

It is possible to notice, from these figures, basic similarities and differences in VPS design from one to another case. Nevertheless, the lack of unified and standardized description method aggravates communication, knowledge and best practice transfer, and at the same time assessment process. Therefore, the need for establishing common mutual describing instrument is quite obvious.

As already stated we have approached the problem using System Engineering methodologies based on SysML modeling language that has been developed during the project and described in previous annual reports and publications [START_REF] Vukmirovic | Software architecture for Smart Metering systems with Virtual Power Plant[END_REF][START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF]. Finally bringing all together, abstract model and selected best-practice implemented solutions, the reference model has been built. The working version of the model has been reconsidered by the partners several times (according to Systems Engineering practice [START_REF] Weilkiens | Systems Engineering with SysML/UML: Modeling, Analysis, Design[END_REF]) and eventually the VPS reference model in Fig. 7 has been obtained as the recommended optimal solution accepted by entire AlpEnergy consortium. Each of these layers represents a functional block in VPS design (note that functionalities that are grayed out are deemed optional in VPS operation). Considering the model in Fig. 2, it should be noted that it considers even foreseen future scenarios (e.g. deregulated energy market that requires trading functionalities) which results in components that are considered but not yet implemented (given in blue color). In the following we explain structure and certain components of the model in greater detail:

Control Center (CC): is responsible of controlling and managing various VPS operations, both commercially and technically related. The heart of CC represents VPS Manager composed of different components performing specific functionalities of VPS Manager. It acts as the VPS interface with the Smart Grid, as well as coordination unit among various specific subunits. From the commercial perspective, the Trading Agent component performs energy price negotiations and contracting with the appropriate counterpart in Smart Grid. Efficient negotiation process requires precise information on current and predicted grid balance (Trading Agent obtains this information from the appropriate components of the VPS). Once the compromise is reached the contract valid for certain period of time is made. This process is described using use case and sequence diagram given in Fig. 4. Upon achieving of external pricing contract (between VPS i.e. Trading Agent and the rest of Smart Grid) the predicted energy balance is then used as an input for the Tariff Manager that calculates the internal energy prices separately for each aggregated VPS user (consumer, producer or prosumer) based on another input coming from Demand Side Management (DSM) component. The DSM based on statistics, predictions, system balance and user portfolios provides customers with tailored incentive plans -informs on energy price trends; applies penalty plans in cases of contract violation and so forth. Billing Manager is responsible for producing the invoices which are eventually communicated to customers through user communication interface (e.g. SMS or a web portal). The Technical Operation Manager acts as an executive unit on demand from VPS Manager, it may also take part in contracting process supplying information on technical feasibility of specific requests. It performs different fundamental grid operations like DER management, Smart Appliances control, power flows and outages management etc. Communication and Data Acquisition layer: The advanced metering infrastructure (AMI) is the interface through which smart meter readings and other status monitoring data are gathered, stored, preprocessed and communicated in understandable form to the VPS Manager. It is rather vendor depended structure but due to increased penetration of standardization also in this segment of power system several crucial standard components have been identified for most of implementations. The Data Concentrator (DC) gathers smart meter measurements and stores the data in structured and standardized fashion into the Database which maintains the web portal configuration as well as administrative data arranged according to customers IDs. In some implementations, the database block can be part of the CC, rather than data acquisition one. Meter Data Management (MDM) further process the data on different granularity levels (i.e. from appliances to DER level), filters them by time period and presents them in a required structured form to CC components. VPS deals with integration of many different technologies so that it should support system like Supervisory Control and Data Acquisition (SCADA) module to work as a data bridge/interface between field devices and the VPS manager.

Field Devices -backend layer: This layer considers backend embedded systems which measure, control or actuate electro-mechanical devices directly attached to the energy entities (energy entities may be -generators, home appliances, storages etc.). These embedded systems include smart meters, PLC (Programmable Logic Controllers), RTU (Remote Terminal Units), 'smart sockets' and so forth. The devices from this layer translate the control signals received directly from the VPS manager (or Local Energy Management in case of distributed control) into an action (e.g. reduce power level, disconnect/reconnect customer etc.). The Local Energy Management unit provides local control decision based on user preferences and constraints but also requests from VPS Manager.

Assessment of ICT solutions

The assessment process has been agreed to be done in three phases:

 Development of a reference model  Development of specific implementations' models according to same principles and standards  Comparison of these two kinds of models by mapping a model of specific case into reference model according to defined standards  Bearing in mind the reference model represented in Fig. 7. and details provided by each partner, appropriate models of pilot implementations have been developed. It can be noted that all the considered case have some differences in the implementation but still the basic structure was preserved. The exact models are result of technical documentation studding and direct interviews with implanting partners.

We present here assessment of one implementation that we consider as the most demonstrative. The assessment models of all other implementations are given in Al-pEnergy Report [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF].The implementation to be assessed has been the one from the Allgäu region [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF]. It has been considered as the most mature pilot and like this also served for the reference model development. The implementation reflects very well conceptual solutions even though some considered solutions like Trading Agent and Local Energy Manager are not fully implemented. The implemented VPS comprises different kind of generators (like PV cells, windmills etc.), Smart Homes, dynamic tariffs management, some elementary DSM and so forth. The detailed assessment report for all the pilot implementations in SysML fashion, is given in [START_REF] Lukovic | AlpEnergy: Virtual Power System (VPS) as an Instrument to Promote Transnational Cooperation and Sustainable Energy Supply in the Alpine Space -Rapport final[END_REF].

Conclusion

In this paper we have presented how system engineering methodology can be efficiently adapted and applied for the design and assessment of a critical structure that is a virtual power system. Even though, due to the size of the system we focus only on functional requirements and structural model of the system in this work, similar methodology can be applied to ensure that critical non-functional properties of the system have been achieved. Given reference model is highly scalable and easily can be extended to support more both functional and non-functional requirements. As a future work, we plan to asses availability and safety of implemented solutions.

Fig. 1 .

 1 Fig. 1. -Internal and external contracting

Fig. 2 .

 2 Fig. 2. -VPS ICT infrastructure -general reference model


Konstantinos Manousakis
email: manousakis.konstantinos@ucy.ac.cy

Georgios Ellinas
email: gellinas@ucy.ac.cy

Design of Attack-Aware WDM Networks Using a Meta-heuristic Algorithm

Keywords: physical layer attacks, routing and wavelength assignment, harmony search, optical networks

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Optical networks nowadays rely on Wavelength Division Multiplexing (WDM) in order to increase their capacity. WDM enables different connections to be established concurrently through a common fiber, subject to the distinct wavelength assignment constraint; that is, the connections sharing a fiber must occupy separate wavelengths. All-optical WDM channels that may span multiple consecutive fibers are called lightpaths. In the absence of wavelength conversion, a lightpath must be assigned a common wavelength on each link it traverses; this restriction is referred to as the wavelength continuity constraint. Since lightpaths are the basic switched entities of a WDM optical network architecture, their effective establishment and usage is crucial.

It is thus important to propose efficient algorithms to select the routes for the connection requests and to assign wavelengths on each of the links along these routes, among the possible choices, so as to optimize a certain performance metric. This is known as the routing and wavelength assignment (RWA) problem [START_REF] Ramaswami | Routing and wavelength assignment in all-optical networks[END_REF], that is usually considered under two alternative traffic models. Offline (or static) lightpath establishment addresses the case where the set of connections is known in advance, usually given in the form of a traffic matrix that describes the number of lightpaths that have to be established between each pair of nodes. Dynamic (or online) lightpath establishment considers the case where connection requests arrive at random time instants, over a prolonged period of time, and are served upon their arrival, on a one-by-one basis.

Offline RWA is usually used during the network design and planning phase, while online RWA is used during the network operation phase.

Offline RWA is known to be an NP-hard optimization problem and several heuristics and meta-heuristics have been proposed to solve the problem. A meta-heuristic is a procedure designed to find a good solution to a difficult optimization problem. Meta-heuristic algorithms can be classified as swarm intelligent techniques and evolutionary algorithms. Swarm intelligence algorithms are heuristic search methods that mimic the metaphor of natural biological evolution and/or the social behavior of species. Evolutionary algorithms use iterative progress, such as growth or development in a population and use mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are well-known and successful swarm intelligence optimization algorithms, while Genetic Algorithms (GAs) and Harmony Search (HS) are evolutionary optimization techniques. Meta-heuristic techniques that have been proposed to solve the offline RWA problem use techniques from ACO [START_REF] Haijin | Ant colony optimization for dynamic RWA in WDM networks with partial wavelength conversion[END_REF], GA [START_REF] Monoyios | Multiobjective genetic algorithms for solving the impairmentaware routing and wavelength assignment problem[END_REF], and PSO [START_REF] Martins-Filho | Intelligent and fast IRWA algorithm based on power series and Particle Swarm Optimization[END_REF].

Optical telecommunication networks, providing services to users such as companies, governmental institutions, and private citizens, are considered one of the critical infrastructures of a country. In all-optical transparent networks, where a data signal remains in the optical domain for the entire path, there exist several vulnerabilities in the network that enable malicious signals to propagate through several parts of the network. Optical networks need to be able to detect and locate failures (faults or attacks) and degradations as fast and as accurately as possible, in order to restore lost traffic and repair the failure. An attack can be defined as an intentional action against the ideal and secure functioning of the network.

In this work, a meta-heuristic algorithm is used to solve the static attack-aware RWA problem. In the static case, the set of connections is known in advance and path selection and wavelength assignment are performed offline, aiming at the joint optimization of the lightpaths used by all the connection requests. The objective of the proposed offline attack-aware RWA algorithm is to design an optical network that minimizes the impact of a network attack. The algorithm uses a nature inspired metaheuristic, mimicking the improvisation process of music players [START_REF] Geem | A new heuristic optimization algorithm: Harmony search[END_REF], known as a harmony search (HS) algorithm. The proposed attack-aware heuristic algorithm serves sequentially the connections in a particular order, and the HS algorithm is used to find better orderings.

The rest of the paper is organized as follows. Section 2 describes the physical layer attacks. In Section 3, the Harmony Search meta-heuristic and Harmony Search based attack-aware RWA algorithm are presented, followed by simulation results in Section 4. Finally, Section 5 presents some concluding remarks and avenues for future research.

Network Attacks

There are several physical layer attacks that can occur in transparent optical networks as presented in [START_REF] Médard | Security issues in all-optical networks[END_REF][START_REF] Mas | Optical networks security: A failure management framework[END_REF]. One of the most important attacks is in-band jamming that is the result of intra-channel crosstalk between the same wavelengths in optical switches. Another attack is the out-of-band jamming, where high-power signals can introduce nonlinearities, causing crosstalk effects between channels on different wavelengths in the same fiber (inter-channel crosstalk). Moreover, gain competition in optical amplifiers is another possible form of attack in optical networks, where a high-power jamming signal can increase its own power, thus resulting in reduction in the gain of the rest of the channels.

Fig. 1. High-power jamming attack propagation

In Fig. 1, the effects of in-band and out-of-band crosstalk propagation are depicted, where an attacker uses a high-power jamming signal on wavelength λ 1 to perform his attack from node n 2 . Due to in-band crosstalk, this signal will affect any lightpath that crosses node n 2 and uses wavelength λ 1 . Then, the affected lightpaths will perform further attacks through the nodes they cross. As can be seen from Fig. 1, the affected lightpath in node n 2 will spread the attack in node n 4 and will affect other lightpaths that use the same wavelength (λ 1 ). A lightpath that uses a different wavelength than the lightpath used by the attacker will not be affected, regardless of the fact that the lightpaths cross the same node. However, due to out-of-band crosstalk, a lightpath at one wavelength will affect any other lightpath using an adjacent wavelength of the same fiber. For example, in Fig. 1, the lightpath crossing node n 3 and wavelength λ 2 , will be affected by the attacker, assuming that the two lightpaths use the same fiber after node n 3 (λ 1 and λ 2 are adjacent wavelengths).

When planning an optical network, the basic problem that has to be addressed is the RWA problem. Since in optical networks security of the established connections is critical, it is of paramount importance to protect the network from possible attacks. The concept of preventive, attack-aware RWA problem was proposed in [START_REF] Skorin-Kapov | A new approach to optical networks security: Attack-aware routing and wavelength assignment[END_REF]. In that work, the authors formulated the routing sub-problem of RWA as an integer linear program with the objective of decreasing the potential damage of jamming attacks causing out-of-band crosstalk in fibers and gain competition in optical amplifiers. A tabu search heuristic was subsequently proposed to cover larger network instances. Furthermore, in [START_REF] Furdek | Attack-aware wavelength assignment for localization of in-band crosstalk attack propagation[END_REF], authors proposed a wavelength assignment approach to limit the potential propagation of in-band crosstalk attacks through the network. Authors in [START_REF] Skorin-Kapov | Wavelength assignment for reducing in-band crosstalk attack propagation in optical networks: ILP formulations and heuristic algorithms[END_REF] extended upon their work in [START_REF] Furdek | Attack-aware wavelength assignment for localization of in-band crosstalk attack propagation[END_REF] by considering a more realistic case where crosstalk attacks can maximally spread in one or two steps. This means that secondary attacked signals are not strong enough for the attack to propagate further. In [START_REF] Skorin-Kapov | Wavelength assignment for reducing in-band crosstalk attack propagation in optical networks: ILP formulations and heuristic algorithms[END_REF], authors proposed the use of wavelength-selective optical attenuators as power equalizers inside the network nodes to limit the propagation of high-power jamming attacks. They presented heuristic algorithms with the objective of minimizing the number of power equalizers needed to reduce, to a desired level, the propagation of highpower jamming attacks.

This work considers that an attack is performed by high-power jamming signals through in-band crosstalk and the objective of the proposed offline attack-aware RWA algorithm is to design an optical network that minimizes the impact of a highpower in-band jamming attacks.

Harmony Search Algorithm

This section describes the Harmony Search (HS) meta-heuristic algorithm as presented in [START_REF] Geem | A new heuristic optimization algorithm: Harmony search[END_REF]. HS is a search heuristic algorithm based on the improvisation process of jazz musicians. It was inspired by the observation that the aim of music is to search for a perfect state of harmony. Finding the perfect state of harmony in music is analogous to finding the optimality in an optimization process. In the HS algorithm, each musician (= decision variable) plays (= generates) a note (= a value) for finding the best harmony (= global optimum determined by objective function evaluation). The core part of the HS algorithm is the Harmony Memory (HM), where HM is a collection of random generated harmonies (=vectors). When a musician is improvising, there are three possible choices: (1) play any famous piece of music exactly from harmony memory; (2) play something similar to a known piece; or (3) compose new or random notes. Authors in [START_REF] Geem | A new heuristic optimization algorithm: Harmony search[END_REF] formalized these three options into a quantitative optimization process, and the three corresponding components become: usage of harmony memory, pitch adjusting, and randomization. Thus, harmony search tries to find a vector X which optimizes a certain objective function f(X). The steps of the harmony search algorithm are as follows:

1. Initialize the harmony memory (HM) matrix:

HM=� 𝑥𝑥 1 1 ⋯ 𝑥𝑥 𝑆𝑆 1 ⋮ ⋱ ⋮ 𝑥𝑥 1 𝐻𝐻𝐻𝐻𝑆𝑆 ⋯ 𝑥𝑥 𝑆𝑆 𝐻𝐻𝐻𝐻𝑆𝑆 � ⇒ � 𝑓𝑓(𝑋𝑋 1 ) ⋮ 𝑓𝑓(𝑋𝑋 𝐻𝐻𝐻𝐻𝑆𝑆 ) � Generate HMS (Harmony Memory Size) random vectors X 𝑖𝑖 = �𝑥𝑥 1 𝑖𝑖 , 𝑥𝑥 2 𝑖𝑖 , … ,

Update the ΗΜ:

Evaluate the objective function 𝑓𝑓(X 𝑛𝑛𝑛𝑛𝑛𝑛 ) of the vector X 𝑛𝑛𝑛𝑛𝑛𝑛 . If the value of 𝑓𝑓(X 𝑛𝑛𝑛𝑛𝑛𝑛 ) is better than the worst value 𝑓𝑓(X 𝑛𝑛𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 ) in HM, then replace the vector X 𝑛𝑛𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 with X 𝑛𝑛𝑛𝑛𝑛𝑛 in HM. 4. Check the stopping criterion:

Repeat steps 2 and 3 until the maximum iteration criterion is met. The exact values of the parameters are discussed in Section 5.

4

Attack-aware RWA using a Meta-Heuristic Algorithm

The proposed algorithm solves the static RWA problem with the objective to minimize the impact of high-power jamming signals that spread in the network through inband channel crosstalk. The attack-aware heuristic algorithm establishes the requested connections one-by-one in the form of lightpaths following a specific order. For every demand, the algorithm computes a set of candidate lightpaths. From this set, the lightpath with the minimum in-band crosstalk interaction is chosen. By minimizing the in-band channel crosstalk interactions, the spread of high-power jamming signals through in-band crosstalk is also minimized. The harmony search metaheuristic is used to define different orderings for the requested connections. The evaluation of the objective function of the harmony search algorithm f(X) is performed through simulation of the attack-aware heuristic algorithm. The ordering with the best value of the objective function is chosen to establish the demands. In the following subsections the main steps of the algorithm are described.

Initialization of Harmony Memory (HM)

For solving the attack-aware RWA problem using HS (Harmony Search), HMS (Harmony Memory Size) random music harmonies (random harmony vectors -X 𝑖𝑖 , 1≤ 𝑖𝑖 ≤ 𝐻𝐻𝐻𝐻𝑆𝑆) are initially constructed and stored in the Harmony Memory (HM) matrix. Each harmony vector X 𝑖𝑖 = �𝑥𝑥 1 𝑖𝑖 , 𝑥𝑥 2 𝑖𝑖 , … , 𝑥𝑥 𝑆𝑆 𝑖𝑖 � in the harmony memory represents the order that the demands are considered. Several values for HMS are discussed in the simulation section. The size S of each vector X i is equal to the number of (s,d) pairs (S=N 2 -N), where N is the number of network nodes, and each element 𝑥𝑥 𝑗𝑗 𝑖𝑖 of the vector X i has an integer value between 1 and (N 2 -N). The sequence of the demands represents a music harmony in HM terminology. In order to have valid sequences for each harmony, each harmony should contain all the integers from 1 to (N 2 -N) and each integer should appear only once. Based on these constraints, all the requested connections are considered. A sequence is invalid if there are two or more integers with the same value.

Improvisation of a New Harmony

A new harmony is improvised (a New Harmony vector X new is generated) based on the HMCR (Harmony Memory Considering Rate) and PAR (Pitch Adjusting Rate) described in Section 3. Each New Harmony vector

X 𝑛𝑛𝑛𝑛𝑛𝑛 = �𝑥𝑥 1 𝑛𝑛𝑛𝑛𝑛𝑛 , 𝑥𝑥 2 𝑛𝑛𝑛𝑛𝑛𝑛 , … , 𝑥𝑥 𝑁𝑁 2 -𝑁𝑁 𝑛𝑛𝑛𝑛𝑛𝑛 �
must comply with the constraints provided in Section 4.1. For this reason, when considering a new value for each variable 𝑥𝑥 𝑗𝑗 𝑛𝑛𝑛𝑛𝑛𝑛 from the set of integer values from 1 to (N 2 -N), the values that have already assigned to variables 𝑥𝑥 1 𝑛𝑛𝑛𝑛𝑛𝑛 , … , 𝑥𝑥 𝑗𝑗 -1 𝑛𝑛𝑛𝑛𝑛𝑛 are removed from the available set. The HMCR, which ranges from 0 to 1, defines the probability to choose a variable value from HM and the PAR defines the probability of shifting to neighboring values within a range of possible values. If the New Harmony vector is better, in terms of the objective function cost f(X new ) as presented in Section 4.3 that follows, than the worst harmony vector in HM, then the New Harmony vector is included in HM while the worst is excluded.

Objective Function -Attack-aware Heuristic Algorithm

This section describes the evaluation of the objective function f(X) used by the harmony search algorithm. Each link l of the network is characterized by a Boolean wavelength availability vector 𝑛𝑛 𝑙𝑙 = [𝑛𝑛 𝑙𝑙𝑖𝑖 ] = (𝑛𝑛 𝑙𝑙1 , 𝑛𝑛 𝑙𝑙2 , … , 𝑛𝑛 𝑙𝑙𝑙𝑙 ) whose i th element li w is equal to 0 if the i th wavelength of link l is utilized by a connection, and equal to 1, otherwise. In this phase, k candidate paths P sd , that have been pre-computed in the first step of the algorithm by employing a k-shortest path algorithm, are given as input in the attack-aware heuristic algorithm for serving each requested connection (s,d). The wavelength availability vector of a path p consisting of links l∈p is defined as follows:

𝑙𝑙 𝑝𝑝 = �𝑙𝑙 𝑝𝑝𝑖𝑖 � = & 𝑙𝑙𝑝𝑝 𝑛𝑛 𝑙𝑙 = [& 𝑙𝑙𝑝𝑝 𝑛𝑛 𝑙𝑙𝑖𝑖 ],
where "&" denotes the Boolean AND operation. Thus, the element W pi is equal to 1 if wavelength i is available for transmission over path p. The above equation enforces the wavelength continuity constraint among the links comprising a path.

The connections are sequentially established one-by-one in the form of lightpaths. The demands are served according to the order defined by the Harmony Vector. For each demand, the candidate lightpath with the smallest number of in-band channel interactions is chosen. The objective of the attack-aware RWA heuristic algorithm is to minimize the number of lightpaths that interact with other lightpaths through inband channel crosstalk and thus to minimize the propagation of high-power jamming signal attacks.

Flowchart of the Algorithm

The flowchart of the algorithm described in the previous subsections is given in Fig. 2. The generation of a new vector X new is achieved following the second step of the algo-rithm described in section 3, taking into account the constraints of section 4.2. Moreover, the evaluation of the objective function f(X) is performed following the description of section 4.3.

Input: G=(V,E) //

Simulation Results

To evaluate the performance of the proposed algorithm, a number of simulation experiments were performed using the generic Deutsche Telekom backbone network (DTnet) as shown in Fig. 3. The network consists of 14 nodes and 23 links with an average nodal degree of 2.85. The traffic load of the network is defined as the ratio of the number of requested connections to the total number of possible connections. For example, traffic load equal to 0.5 corresponds to the case were half of the entries of the traffic matrix are equal to 1 and half equal to 0.

The aim of this section is to study the impact of high-power jamming signals through in-band crosstalk and the evolution of the algorithm solution under different settings of the three important parameters: the pitch adjusting rate (PAR), the harmony memory size (HMS), and the harmony memory considering rate (HMCR). The number of maximum iterations was considered equal to 100, that corresponds to the stopping criterion of the algorithm. First, a sensitivity analysis of the harmony search model parameters was performed. Table 1 shows the results for several values of the parameters (HMS = {1, 5, 10}, HMCR = {0.5, 0.8, 0.9}, and PAR = {0.1, 0.4, 0.7}).

Table 1. Results of sensitivity analysis with HS parameters.

HMS HMCR PAR In-band W=30

In-band W=40 Fig. The term "In-band" in Table I, represents the total number of lightpaths' interactions through in-band crosstalk. The network load was equal to 0.6 and the analysis was performed for the cases of 30 and 40 available wavelengths per fiber. It is evident, that the larger the HMCR value, the less exploration is achieved; and the algorithm further relies on stored values in HM and this potentially leads to the algorithm reaching and remaining at a local optimum. On the other hand, choosing too small a value of HMCR will decrease the algorithm efficiency and the HS will behave like a pure random search, with less assistance from the historical memory.

Fig. 4. In-band interactions vs number of available wavelengths

In Fig. 4, the HS attack-aware RWA algorithm was also compared to the first-fit algorithm, an algorithm that assigns the first available wavelength to the connections. The performance metric in this case was the number of in-band interactions versus the available number of wavelengths per fiber. For these simulations the network load was again equal to 0.6 and the three parameters used for the HS meta-heuristic, i.e., the pitch adjusting rate (PAR), the harmony memory size (HMS), and the harmony memory considering rate (HMCR) were set to the values 0.1, 5, and 0.8 respectively. These values were obtained from the sensitivity analysis as shown in Table 1 above.

As can be seen from the figure, the first-fit algorithm has the same performance irrespective of the number of available wavelengths and the number of interactions is quite high (more than 600 interactions) compared to the case were the proposed HS attackaware RWA algorithm was used. For the latter case it is shown that the proposed technique clearly outperforms the traditional RWA approach, minimizing the in-band channel interactions based on the available wavelengths. Thus, with the proposed approach the attack is contained, and it is not allowed to propagate extensively in the network, resulting in degradation of the established network connections.

Conclusions

This work proposed an algorithm for solving the RWA problem during the design phase of a transparent WDM optical network with the objective of minimizing the high-power in-band crosstalk propagation which is caused when a high-power jamming signal is maliciously introduced in the network at a specific network node. A meta-heuristic approach based on the harmony search technique is utilized to obtain an ordering of the connection requests and this ordering is used during the RWA algorithm to establish all requested connections in the network. Performance results indicate that the proposed solution outperforms the traditional RWA technique that does not account for the propagation of the jamming signal due to intra-channel crosstalk, significantly minimizing this propagation in the network and thus drastically containing the effect of the attack on the network infrastructure. Current ongoing research work on this subject focuses on the effects of inter-channel crosstalk attack propagation, as well as on the design of integer linear programming (ILP) formulations for the RWA problem, aiming at minimizing the attack propagation.

  𝑥𝑥 𝑆𝑆 𝑖𝑖 � of size S and store them in the harmony memory (HM) matrix, where S is the number of musical instruments (decision variables, 𝑥𝑥 𝑗𝑗 𝑖𝑖 ) and HMS is the number of random harmonies (vectors). f(X) is the objective function that needs to be optimized. 2. Improvise a new harmony (Generate a new vector X 𝑛𝑛𝑛𝑛𝑛𝑛 ) (a) For every variable 𝑥𝑥 𝑗𝑗 𝑛𝑛𝑛𝑛𝑛𝑛 of the new vector X 𝑛𝑛𝑛𝑛𝑛𝑛 choose a value from the HM

	𝑛𝑛𝑛𝑛𝑛𝑛 with probability PAR (Pitch Adjusting (b) Change the value of the variable 𝑥𝑥 𝑗𝑗 Rate), by a small amount Δ, 𝑥𝑥 𝑗𝑗 𝑛𝑛𝑛𝑛𝑛𝑛 = 𝑥𝑥 𝑗𝑗 𝑛𝑛𝑛𝑛𝑛𝑛 ± Δ.
	matrix 𝑥𝑥 𝑗𝑗 𝑛𝑛𝑛𝑛𝑛𝑛 , 1 ≤ 𝑛𝑛𝑛𝑛𝑛𝑛 ≤ 𝐻𝐻𝐻𝐻𝑆𝑆 with probability HMCR (Harmony Memory
	Considering Rate) and with probability 1-HMCR, choose a random value.

  Harmony Memory) matrix with HMS random vectors X of size N 2 -N. Each vector should contain all the integer values from 1 to N 2 -N. Each vector contains the order of the demands that have to be establishedFor each vector X calculate the cost of the objective function f(X) and sort the vectors in ascending order based on the cost of the objective function f(X best )<f(X worst )Generate a new vector X new considering the HM with probabilities HMCR and PAR as described in the second step of the HS algorithm of Section 3 f(X new )<f(X worst ) Replace X worst with X new in HM and place X new in the proper place based on the cost of f(X new )

	Start
	Network
	Λsd //traffic matrix
	HMS // Harmony Memory Size
	HMCR // Harmony Memory Consideration Rate
	PAR // Pitch Adjusting Rate
	For each source destination (s-d) pair compute k candidate paths
	YES Initialize HM (Maximum iterations NO	NO
	reached
	YES
	Return f(X best )
	End
	Fig. 2. Flowchart of the algorithm

Acknowledgment: This work was supported by the Cyprus Research Promotion Foundation's Framework Programme for Research, Technological Development and Innovation (DESMI 2008), co-funded by the Republic of Cyprus and the European Regional Development Fund, and specifically under Grant Project New Infrastructure/ Strategic/0308/26).


Panagiota Simou
email: simou@ionio.gr

Konstantinos Tiligadis

Athanasios Alexiou
email: alexiou@ionio.gr

Exploring Artificial Intelligence Utilizing BioArt

Keywords: Artificial Intelligence, BioArt, Bioethics, Post humanism

While artificial intelligence combined with Bioinformatics and Nanotechnology offers a variety of improvements and a technological and healthcare revolution, Bioartists attempt to replace the traditional artistic medium with biological materials, bio-imaging techniques, bioreactors and several times to treat their own body as an alive canvas. BioArt seems to play the role of a new scientific curator in order to manipulate laboratory aesthetics and bridge transhumanism creations with culture and tradition.

Introduction

"…υπό δ΄ αμφίπολοι ρώοντο άνακτι χρύσειαι, ζωήσι νεήνισσιν εϊκυίαι της εν μεν νοός εστί μετά φρεσίν, εν δε και αυδή και σθένος…". As indicated in the Greek mythology, Talos is said to be the first Artificial Intelligence Robot that Hephaestus created in his ancient lab, as well as golden maids who could move, speak and think like human beings and tripod tables for the automatic transfer of food and drink to gods. It seems that the necessity of creating metallic assistants-robots constitutes a spontaneous attribute of human culture and temperament with roots reaching back to the dawn of our civilization.

According to Humanism, human beings have the right and responsibility to give meaning and shape to their own lives, building a more humane society through an ethic based on human and other natural values in the spirit of reason and free inquiry through human capabilities. The moral person guided from his evolving social behavior, can easily comprehend and be committed to laws and principles that a scientific field, such as Artificial Intelligence (AI) or Nanoscience set as a precondition, in order to improve the structural elements of human biological existence [START_REF] Alexiou | 7th Artificial Intelligence Applications & Innovations[END_REF][START_REF] Alexiou | Ethics at the Crossroads of Bioinformatics and Nanotechnology[END_REF].

The fact of the upcoming era of Post humanism, hypothetical raises various questions and bioethical issues, such as the degree of influence of human consciousness, dignity, rights and fundamental freedoms by merging human beings and machines. Additionally, the Universal Declaration of Human Rights on genetic data defines personal identity as a combination of distinctive genetic makeup with educational, environmental, personal, emotional, social, spiritual and cultural factors.

Modern sciences that complement Medicine and Biology, such as Nanotechnology, Bioinformatics, stem cell technology, transgenic organisms, neural prosthetics and AI applications, have enhanced human intelligence, offering new possibilities for the human body, documenting the potential immortality of our biological existence. Thus a series of philosophical questions and ethical considerations rises through these innovative applications of human intellect. Bioethics, as a field of philosophical and critical approach, have an essential duty to contribute to the regulatory investigation of ethical issues rising from biomedical applications, but also to clarify the relationship between the life sciences and art, as is now expressed through biotechnology.

Artists involved in biological sciences, have now adopted a very unique way of expression, while laboratory components have already become an integral part of the artistic process or art masterpieces, a few times. It is a fact, the presence of artists in modern biological laboratories, in order to overcome the well-known effects and decorative of Fine Arts and manipulate life. BioArt is not a simple theme or artistic movement, but a complex tool for creating projects such as: use and transplant of mechanical devices in humans, creation of robot-clones etc.

Super Intelligence in the Post Mondo

By definition super intelligence is any intellectual component that generates the best human brains, including scientific creativity, general wisdom, and social skills [START_REF] Bostrom | How Long Before Super intelligence?[END_REF].

Obviously super intelligence can produce new knowledge and solutions to hard i.e. a smart Nano machine can recognize cancer cells using the tunneling phenomenon, or a machine learning algorithm could give right decisions in the forecast of neurogenerative diseases like epilepsy [START_REF] Alexiou | 7th Artificial Intelligence Applications & Innovations[END_REF].

On the other hand the parallel innovating structure of the so called 'convergent technologies', referring to the NBIC tools and including Nano science and nanotechnology, biotechnology, biomedicine and genetic engineering, information technology and cognitive science, seems to remove any barrier in scientific and technological achievement [START_REF] Roco | Converging technologies for improving human performance[END_REF]. The Nano devices which can repair cells, promise great improvements in longevity and quality of life, involving radical modifications of the human genome and leading to the old but diachronic issue of human immorality [START_REF] Drexler | Engines of Creation[END_REF].

Unlike mankind, AI applications can use and manipulate the storage knowledge through scientific or social networks in a more efficient way. Therefore one of the best ways to ensure that these super intelligent creations will have a beneficial impact on the world is to endow it with philanthropic values and friendliness [START_REF] Kurzweil | The Age of Spiritual Machines: When Computers Exceed Human Intelligence[END_REF]. Additionally, super intelligence could give us indefinite lifespan, either by stopping and reversing the aging process through the use of Nano medicine [START_REF] Moravec | Robot: Mere Machine to Transcendent Mind[END_REF].

Often Art is prior to Science and has the ability to envision and create projects which is not yet feasible to be implemented, or be applied in human societies. For all innovative artists, art often works in a Post Mondo ("Perfect Future"), which constitutes the past, from a given starting point onwards.

In other cases Science comes to inspire Art, give stimuli for new ideas and techniques and give new directions in the use of innovative tools and materials. While Science and Art are the most common human types of knowledge and emotional expressions, they have to be perpetually in a dynamic interdependence, interactive communication and exchange principles in order to be more understandable and representative of human existence and dimension.

 It is imperative to answer a series of questions before establishing the hypothetical era of Post Mondo and Super Intelligence:  How the world would like if the scientific achievements were accessible to all people (cloning, production of human organs, personalized gene therapy etc.)?  If for any illness or any form of disability there was a proper treatment, what would be the structure of any future Perfect World?  Human societies will tolerate smart, intelligent and strong members and on what life expectancy?  In human societies of perfect and potentially immortal beings is it possible to adjust the principles of economics and politics and the traditional values of relationships?  While the achievement of human perfection, the progress of genetics, the use of mechanical additives and the creation of transgenic animals improve cell physiology, could this lead to people who will not obey to laws as we know them now?

In order to develop the Perfect-Human, all the human structural elements have to be immortal, overcoming the Central Dogma of Genetics and upsetting the fundamental principles of human evolution. If we also take into consideration the studies of modern genetics on the non-mental and spiritual identification of clones with their original organism (i.e. the case of twins) another important question raises:

 Are there any psycho-spiritual disruptions in cloned organisms or in organisms with prosthetic biological implants?  Have we already excluded the possibility of cultured tissues reaction (i.e. BioArt Semi-Living) with the environment and human actions [START_REF] Zurr | The ethical claims of Bioart: Killing the Other or Self Cannibalism[END_REF]?

The study on perfection's definition and principles consist of a major philosophical enquiry for thousands of years. Is there perfection in Nature and Evolutionary Laws? Perfect creations follow the natural law of evolution or they are kept unaltered in order to remain perfect? Perfection's evolution does ultimately equate with the supernatural?

Seeking for a New Role -Ethical Challenges

The development of nanotechnology is moving rapidly, and without any clear public guidance or leadership as to the moral tenor of its purposes, directions and outcomes; where nanotechnology is leading and what impact it might have on humanity is anyone's guess [START_REF] Berne | Towards the conscientious development of ethical nanotechnology[END_REF]. What appears to be missing at the present time is a clearly articulated prognosis of the potential global social benefits and harms that may develop from further scientific and technological advances in all of these areas [START_REF] Sweeney | Social and Ethical Dimensions of Nanoscale Research[END_REF]. Super Intelligence should be comprehensible to the public, including activities that benefit society and environment, guided by the principles of free participation to all decision-making processes; AI techniques in Biomedicine, should respect the right of access to information, having the best scientific standards and encouraging creativity, flexibility and innovation with accountability to all the possible social, environmental and human health impacts.

BioArt even today, represents all those forms of art, associated in any way with the life sciences, and uses the life and living things both as a medium and as an objects' expression. In the trans human' era, BioArt requires close cooperation between artists and scientists, and also a thorough understanding of the research process, from the artists mainly. Obviously, laboratory techniques associated with biotechnology, such as stem cell research and its applications have already been implemented by specialized scientists around the world. Bio Artists have to communicate and share this scientific knowledge with the society, in the way that they perceive and accept it as part of human evolution. Sometimes hybrid art offers to the audient macabre and repulsive artistic creations, using human body as the basic material like Stelarc, Orlan and Franko-B [START_REF]Stelarc website[END_REF][START_REF]Orlan website[END_REF][START_REF] Website | [END_REF], transgenic art creations like Kac [START_REF] Kac | Transgenic Art[END_REF], Cybernetics technology like Haraway and Warwick [START_REF] Haraway | A cyborg manifesto. Science, Technology and socialist-feminism in the late twentieth century. Simians, Cyborgs and Women: The reinvention of nature[END_REF][START_REF] Warwick | Future issues with robots and cyborgs[END_REF], hyper-real sculptures like Piccinini [17].

BioArt searches for the meaning of human existence in relation to the natural environment and enhances the value of parts of the human body as autonomous and interdependent subsets. Judging from the already registered events and the historical development of Arts today, there is a strong possibility that BioArt outline a total new future serving as a communication channel between science and society, while humans are still trying to conquer the torrent of scientific knowledge.

According to philosopher Nietzsche, the distance that separates Perfect-Man from man is identical to that which separates man from monkey. The transition in a supernatural state involves an evolutionary leap and a profound change in human nature. BioArt is willing to lead this evolutionary perspective, through the expressions of Nanotechnology, Neuroengineering, Bioinformatics, Molecular Biology and Cellular Therapy, but also to establish new rules through the methodological approaches of bioethics.

BioArt must highlight and promote the uniqueness of the individual, to strengthen the role of man in the AI and probably to propose solutions for the improvement and protection of life according to human ideals. In order to achieve this, a dialogue about what is ethical and legal to be expressed through BioArt must start immediately, such as the use of human organs, tissues, blood, bacteria and viruses or even more the intentional infliction of pain.

 Can we assume that BioArt main objectives are the selection of a new way of achieving Post humanity and biological immortality, by not following the common paths of aesthetic expression and traditional -for human senses-beauty?

 Harmony and aesthetic which are features of our nature, is it possible to remain stationary into the acceptable social contexts or will adapt new data and scientific challenges without the discrete and finite limits of human consciousness?  Could harmony and aesthetics reflect human vision and its finite capabilities (human perception of three-dimensions) or are there independent natural rules which are not influenced by our evolution?

It is clearly that BioArt can apply innovative techniques for example on exploiting or creating new sensations in cases of disabled people, in the technological application of the phenomenon of quantum entanglement, in the education process and in support the AI products integration into society (e.g. Robot-clones). BioArt seems to be the play the role of scientific curator presenting the products of AI in an acceptable way for the human brain, providing also a set of principles and rules such as: aesthetics, behavioural properties, boundaries and functions, adaptation and harmonization in customs. Additionally, BioArt should examine the developmental stages of human cognitive and determine ethical and adaptation rules for artificial intelligence's products in human evolution.

Appears however that this new Art, exists only in technologically advanced societies where science works as a tool, raising ethical questions about equality and accessibility on super intelligence among people and nations.

Conclusion

For over 100 years, the scientific activity experiencing such growth, that seems to replace the entire culture. Initially this is an illusion caused by the speed of this development and this qualification triumph that characterizes Science, gave the right to dominate the entire culture. Few researchers also, fearing the domination of society by the science, predict the destruction of culture [START_REF] Prigogine | Order out of Chaos[END_REF]. Science, however changes the 'DNA of our thinking', expression, perception and our aesthetics. Additionally through Art's manipulation, we can compete and imitate nature using AI applications, only if we manage to discover and model mechanisms and structural elements.

According to Zarr and Catts [START_REF] Zurr | The ethical claims of Bioart: Killing the Other or Self Cannibalism[END_REF] it is important to mention that BioArt is a pluralist practice with its artists occupying different ethical positions such as the creation of public acceptance for biotech developments or the generation of heated public debate about their uses.

Therefore it is obviously that many ethical and legal challenges seek for answers concerning BioArt and hybrid art in general and their different approaches from artists, art theorists, curators, ethicists and philosophers, scientists and engineers.


Panayiotis Vlamos
email: vlamos@ionio.gr

Athanasios Alexiou
email: alexiou@ionio.gr

Georgia Theocharopoulou

Ethical issues in Neuroinformatics

Keywords: Neuroinformatics, Artificial Intelligence, Bioethics

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The exploration of brain functions from a variety of fields has led to scientific developments in Artificial Intelligence (AI), like computational methods and systems for learning and knowledge discovery. Neuroinformatics is a research field concerned with the study of neuroscience with the use of information technology. Neuroinformatics organizes and integrates neuroscience data and applies computational tools and mathematical models in order to understand human brain physiology and functionality (Fig 1). According to the International Neuroinformatics Coordinating Facility (INCF) there are three main fields where Neuroinformatics have been applied [START_REF]International Neuroinformatics Coordinating Facility[END_REF]:

 Development of tools and databases for management and sharing of neuroscience data at all levels of analysis  Development of tools for analyzing and modelling neuroscience data  Development of computational models of the nervous system and neural processes.

These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data. Neuroinformaticians provide and create interoperable databases for clinical and research scientists. Therefore, it is necessary to be able to share data and findings. The field of Neuroinformatics came into existence when the Human Brain Project began in the early 1990's. The primary goal of the Human Brain Project and Neuroinformatics is the development of new technologies for creating databases and database search tools, for information exchange of neuroscience data, in order scientists and researchers to build data models of the brain and also create simulations of brain functions [START_REF] Shepherd | The Human Brain Project: Neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data[END_REF]. Neuroinformatics has a variety of applications and uses in both the field of neuroscience and also information technology. Like other new technologies, there are legal and ethical issues that need to be accounted for in order to perform Neuroinformatics' research. There are several opinions on data sharing, and there are legal and ethical issues that need to be accounted for regarding four major key issues:  Gathering data in order to create Neuroscience Databases  Data sharing used in developing tools for analyses, simulation and modelling neuronal functions  Data access in order to protect the subjects included in the data  Legal and ethical issues that need to be accounted for performing research and clinical trials on patients.

Obviously, we have to distinguish the ethics of the productive technologies as a human's risk, from the ethics concerning the scientific and the AI's progress. The use of AI techniques in Neuroinformatics is totally separated from religious sentiments, human dignity or essential emotional states [START_REF] Alexiou | 7th Artificial Intelligence Applications & Innovations[END_REF]. In this article we outline future directions for research regarding ethic challenges in the above mentioned issues.

Legal and Ethical Issues in Neuroinformatics

Data sharing projects include databases designed to archive data sets (e.g. neuroimaging results), and tools for neuroscience data. One major effort supporting integrative neuroscience research is the Neuroscience Information Framework (NIF). Few important aspects to the legal issues associated with Neuroinformatics regarding data and tool sharing are: protection for the creator of the data or tool, protection for the user and protection for the subjects included in the data [START_REF] Amari | Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience[END_REF].

Considering the availability and accessibility of data, it is very important for researchers and users to protect themselves and give credits to the appropriate researchers or institutions responsible for the research. But is this enough in order to achieve balance between the objective of scientific progress and the usage from sensitive groups of population? In which way will it become beneficial for all humans and more feasible to merge the increasing cost of new methods in health diagnosis and treatment, with the accessible and high quality medical care [START_REF] Alexiou | Ethics at the Crossroads of Bioinformatics and Nanotechnology[END_REF]? It is also important for users to know the source of the information in order to be amenable to validation. In the past years there has been introduced national and international data-privacy regulations and Neuroinformatics researchers follow the copyright and intellectual property rights established by the Ethical Review Boards across the world [START_REF] Amari | Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience[END_REF]. While there are regulations and principles formulated with biomedical and social-behavioural research in mind, there are diverse opinions expressed by investigators about the fit between the national regulations and data sharing like: Should public money be spent on Open Access Projects, or how to share legally massive amounts of data?

In some cases further consideration is required; therefore several factors should be considered amongst others:  proprietary information that must be protected  legal and institutional requirements or regulations that need to be established  collection of data, analysis of data, integration of the results into a conceptual model  actual modelling of the experimental result, and development of a scientific manuscript

The above mentioned concepts should be considered in creating principles adequate for enabling collaborative and integrative information sharing in the field of neuroscience studies. The legal issues regarding sharing data have led to more strict and precise rules in order to ensure human subject anonymity and avoid inappropriate use of information. On the other hand international collaborations generated new concerns regarding fulfilment of International Ethical Review Boards requirements.

It is necessary that these cooperative efforts are carried out with similar and clearly defined fields, terminology description of data, models, experimental procedures etc., as well as developing appropriate common guidelines regarding legal issues of sharing and analyzing neuroscience data. Furthermore, credits should be appropriately addressed for both data owner, as well as data user. Some of the challenges regard also issues like the rights of each researcher the purpose of the data sharing, access to data, allocation of rights/ownership etc. Policy makers and developers should consider ethics and policy challenges regarding the following:

 Regulating the content of databases  Access to databases  Use of databases

The researchers should aim to ensure that data remains confidential and simultaneously develop models that fulfil their technical requirements in order to satisfy their expectations.

Regulating the Content of Databases

Image-based data are primary drivers for Neuroinformatics efforts [START_REF] Martone | E-neuroscience: challenges and triumphs in integrating distributed data from molecules to brains[END_REF]. For example the functional Magnetic Resonance Imaging Data Center (fMRIDC) was established with the objective of creating a mechanism by which members of the Neuroscientific community might easily share functional neuroimaging data. Additionally, the Journal of Cognitive Neuroscience between 2000 and 2006 required that all authors who published in the journal submit their supplementary data to the fMRIDC [7]. Authors whose papers are based on results from datasets obtained from the Data Center are expected to provide descriptive meta-information for data use, credit original study authors and acknowledge the fMRIDC and accession number of the data set [START_REF] Illes | Identifiable neuro ethics challenges to the banking of neuro data[END_REF].

It is obvious that researchers using data from digital databases may encounter the risk of discovering violation of the providers' privacy, or disclosure of sensitive information. Since Neuroinformatics worldwide repositories will be populated by data, standardization of protocols for managing incidental findings, and limitation to the risk of intrinsic and consequential harm of donor are necessary. Ethical principles should enhance regulations for protecting human research participants, so as data sharing will always be safe and efficient.

Another issue that should be considered in neuroimaging sharing is the quality control of brain imaging data. Appropriate cautions should be applied in the use of these data, when predicting for example, diseases of the CNS. Concerns about the use of functional Magnetic Resonance Imaging (fMRI) scans of adolescents to predict later onset psychiatric disorders are referred in [START_REF] Fuchs | Ethical issues in neuroscience[END_REF] regarding the reliability of neuroimaging due to the complexity and plasticity of the brain.

It is obvious that the hybrid ethical codes concern early diagnosis of CNS diseases differ from Neuroinformatics to traditional medicine approach due to the influence of other ethical frameworks and perspectives on their basic research and development. For some, this information could be helpful, empowering or enlightening and may enhance human health. For others, it is likely that such information could result in fear, anxiety and other mental health issues [START_REF] Alexiou | 7th Artificial Intelligence Applications & Innovations[END_REF].

Access and Use of Databases

Artificial Intelligence research is undergoing a revolution in the area of understanding the mechanisms underlying intelligent behavior. Internet-accessibility of databases has enabled the usage of data from providers, patients, and research participants everywhere. Research studies involve a degree of trust between subjects and researchers, the former giving their consent and the latter protecting their privacy [START_REF]International Neuroinformatics Coordinating Facility[END_REF]. Different countries have various regulations and procedures regarding ethical issues of human data sharing:

 The federal human subject protection law in the United States mandates that all identifying information be removed from data prior to submission for sharing [START_REF] Wolf | Untapped Potential: IRB Guidance for the Ethical Research Use of Stored Biological Materials[END_REF].  Additionally, Institutional Review Boards (IRB) are administrative bodies in the U.S., established to protect the rights and welfare of human research subjects and are designated to review clinical investigations regulated by U.S. Food and Drug Administration (FDA).

A major continuing goal of these boards is to ensure that national guidelines for protection of privacy and informed consent are best applied in the development of neuroscience data repositories. However, technical issues might arise, like the case where researchers wish to share retrospective data and process the way to obtain a new written informed consent. For example, the steering committee of the 1000 Functional Connectomes Project (FCP), a data sharing initiative project, realizing the necessity for privacy, agreed to a full anonymization of all datasets in accordance with the U.S. Health Insurance Portability and Accountability Act (HIPAA) [START_REF] Maarten | Making data sharing work: The FCP/INDI experience[END_REF].

Another aspect that raises further ethical issues is commercialization of databases. What details are necessary to share in data exchange and scientific results? The challenge is how to prevent exploitation of vulnerable populations, and avoid conflicts of interest. Data storing and data sharing can be both a challenge and a desire in for scientific researchers. The research of hybrid ethics in Neuroinformatics tools has to examine the malpractices during the past years in order to explore efficient and effective ways to accomplish data organization with ethical use of data. There is a worldwide debate about principles and regulations for the scientific processes. Guidance is needed to protect against discriminatory practices in case of commercialization of data sharing, as well as for issues regarding ownership and intellectual property of results and follow on innovation. A 'clear' definition on using and sharing data and meta-data seems to be necessary.

Conclusion

The next generation of neuroscientists contributes to a worldwide research network of excellence sharing data, tools, and information. Success on data sharing depends on the participation of the different types of neuroscience researchers. There should be considered a more critical thinking on searching for neuroscience relevant resources, including the ethical aspect. There is a major challenge in developing large-scale international collaborations and there is significant effort in developing integrated models of neuroscience processes. The more informed our brains are by science at all levels of analysis, the better will be our brains theoretical evolution [START_REF] Maarten | Making data sharing work: The FCP/INDI experience[END_REF]. Neuroinformatics can play a pivotal role in human brain research leading to innovations in neuroscience, informatics and treatment of brain disorders. Guidance to investigators, IRB representatives, public health officials and others regarding bioethics are key issues in neuroscience data sharing.

Fig. 1 .

 1 Fig. 1. Neuroinformatics Research Fields