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Software systems and computational methods
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Yur'eva R.A., Komarov I.I., Maslennikov O.S. Development of the method for detection and identification of hidden destructive impact on the multi-agent robotic systems

Abstract: Increased information security risks in multi-agent robotic systems create a need for new and known assessment in terms of security algorithms. Such risks include the loss or inaccessibility of data, spreading false information about the purpose of grouping and the use of distorted information, lack of energy resources. Authors note that common approaches to information security in multi-agent robotic systems so far are not formed. The research is aimed at developing a model of information security in multi-agent robotic systems taking into account the specifics of the technology. Existing scientific and methodical apparatus and technical solutions of ensuring information security in multi-agent systems are not applicable to the tasks of ensuring information security in multi-agent robotic systems due to the specific technology and a special type of threat models and the offending patterns associated with them. Existing methods of providing information security of multi-agent systems do not provide a comprehensive solution of the problems of information security in the multi-agent robotic systems, since they do not take into account the specificity of their composition and structure. Scientific novelty consists in the development of software models of information security risks in multi-agent robotic systems. An advantage of the method is the ability to detect new types of attacks without having to modify or update the model parameters, since the invasion of the offending system can be described as a deviation from the nominal behavior.


Keywords:

hidden destructive effect, identification of the destructive impact, feature space, informative signs, information attack, data protection, swarm intelligence, information security model, decentralized control, multi-agent robotic system


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References
1. Yurevich E.I. Osnovy robototekhniki. 2-e izd., pererab. i dop. SPb.: BKhV-Peterburg, 2005. 416 s.
2. Yur'eva R.A., Komarov I.I., Dorodnikov N.A. Postroenie modeli narushitelya informatsionnoi bezopasnosti dlya mul'tiagentnoi robototekhnicheskoi sistemy s detsentralizovannym upravleniem // Programmnye sistemy i vychislitel'nye metody. 2016. ¹ 1(14). S. 42-48
3. Stankevich L.A. Adaptivnye povedencheskie sistemy na neirologicheskikh setyakh. 11-ya Natsional'naya konferentsiya po iskusstvennomu intellektu s mezhdunarodnym uchastiem (KII-08), 29.09-3.10.2008, Dubna. 7 s.
4. Stankevich L.A. Neirologicheskie sredstva sistem upravleniya intellektual'nykh robotov. Nauchnaya sessiya MIFI-2004. VI Vserossiiskaya NTK «Neiroinformatika-2004»: Lektsii po neiroinformatike, ch. 2. M.: MIFI, 2004. S. 57-110.
5. Kolling A., Nunnally S., Lewis M. Towards Human Control of Robot Swarms (2012). [elektronnyi resurs], http://faculty.cs.byu.edu/~mike/mikeg/papers/MOSC/LewisIros11swarm.pdf), rezhim dostupa svobodnyi.
6. Navarro I., Matía F. An Introduction to Swarm Robotics. ETSI Industriales, Universidad Politécnica de Madrid, c/José Gutiérrez Abascal, 2, 28006 Madrid, SpainReceived 18 April 2012; Accepted 19 June 2012 [elektronnyi resurs], http://www.hindawi.com/isrn/robotics/2013/608164/, rezhim dostupa svobodnyi.
7. Knowledge Driven Planning and Modeling. NIST Laboratory. [elektronnyi resurs], http://www.nist.gov/el/isd/ps/knowdrivenplanmodel.cfm, rezhim dostupa svobodnyi.
8. Higgins F., Tomlinson A., Martin K. M., Survey on security challenges for swarm robotics, in Proceedings of the 5th International Conference on Autonomic and Autonomous Systems (ICAS '09), pp. 307–312, IEEE Computer Society, Los Alamitos, CA, USA, April 2009.
9. Gjondrekaj E., Loreti M., Pugliese R., Tiezzi F., Pinciroli C., Brambilla M., Birattari M., Dorigo M. Towards a Formal Verification Methodology for Collective Robotic Systems. In Formal Methods and Software Engineering, Proceedings of the 14th International Conference on Formal Engineering Methods, ICFEM 2012, volume 7635 of Lecture Notes in Computer Science, pages 54-70. Springer, Berlin, Germany, 2012. [elektronnyi resurs], http://code.ulb.ac.be/dbfiles/GjoLorPug-etal2012icfem.pdf, rezhim dostupa svobodnyi.
10. Rubenstein M., Hoff N., Nagpal R. Kilobot: A Low Cost Scalable Robot System for Collective Behaviors. Computer Science Group Harvard University Cambridge, Massachusetts URL: ftp://ftp.deas.harvard.edu/techreports/tr-06-11.pdf (rezhim dostupa: otkrytyi; data obrashcheniya: 13.02.2014).
11. Kalyaev I.A., Gaiduk A.R., Kapustyan S.G. Modeli i algoritmy kollektivnogo upravleniya v gruppakh robotov. M.: FIZMATLIT, 2009. 280 s.
12. Couzin I.D., Krause, J., Franks, N.R. & Levin, S.A. Effective leadership and decision making in animal groups on the move. Nature 433, 513-516, 2005
13. Komarov I.I., Yur'eva R.A., Drannik A.L., Maslennikov O.S. Postanovka zadachi obespecheniya informatsionnoi bezopasnosti roevykh robototekhnicheskikh sistem // Nauka i biznes: puti razvitiya. 2015..¹ 3(45). S. 66-72.