全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
Sensors  2012 

Consolidation of a WSN and Minimax Method to Rapidly Neutralise Intruders in Strategic Installations

DOI: 10.3390/s120303281

Keywords: intelligent systems, wireless sensor network, decision support systems, minimax algorithm, path planning, risk measure, surveillance system

Full-Text   Cite this paper   Add to My Lib

Abstract:

Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective.

References

[1]  Vu, V.T.; Bremond, F.; Davini, G.; Thonnat, M.; Pham, Q.-C.; Allezard, N.; Sayd, P.; Rouas, J.-L.; Ambellouis, S.; Flancquart, A. Audio-Video Event Recognition System for Public Transport Security. Proceedings of the Institution of Engineering and Technology Conference on Crime and Security, London, UK, 13–14 June 2006; pp. 414–419.
[2]  Dollar, P.; Rabaud, V.; Cottrell, G.; Belongie, S. Behavior Recognition via Sparse Spatio-Temporal Features. Proceedings of the 2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, Beijing, China, October 2005.
[3]  Garfinkel, S.L.; Juels, A.; Pappu, R. RFID privacy: An overview of problems and proposed solutions. IEEE Secur. Priv 2005, 3, 34–43.
[4]  Royston, P. RFID Security. Proceedings of the Institution of Engineering and Technology Conference on Crime and Security, London, UK, 13–14 June 2006; pp. 239–257.
[5]  Prabhakar, S.; Pankanti, S.; Jain, A.K. Biometric recognition: Security and privacy concerns. IEEE Secur. Priv 2003, 1, 33–42.
[6]  Conesa, J.; Ribeiro, A. Performing the Retrieve Step in a Case-Based Reasoning System for Decision Making in Intrusion Scenarios. Proceedings of the 11th International Conference on Enterprise Information Systems (ICEIS 2), Milan, Italy, 6–10 May 2009. Volume AIDSS; pp. 343–346.
[7]  Zhenwei, Y.; Tsai, J.J.P.; Weigert, T. An automatically tuning intrusion detection system. IEEE Trans. Syst. Man Cybern. Part B Cybern 2007, 37, 373–384.
[8]  Marcenaro, L.; Oberti, F.; Foresti, G.L.; Regazzoni, C.S. Distributed architectures and logical-task decomposition in multimedia surveillance systems. Proc. IEEE 2001, 89, 1419–1440, doi:10.1109/5.959339.
[9]  Farina, A.; Golino, G.; Capponi, A.; Pilotto, C. Surveillance by Means of a Random Sensor Network: A Heterogeneous Sensor Approach. Proceedings of the 8th International Conference on Information Fusion, Franklin Plaza, PA, USA, 25–29 July 2005; 2, pp. 25–28.
[10]  Liu, Z.; Li, C.; Wu, D.; Dai, W.; Geng, S.; Ding, Q.A. Wireless sensor network based personnel positioning scheme in coal mines with blind areas. Sensors 2010, 10, 9891–9918, doi:10.3390/s101109891. 22163446
[11]  Maki, M.; Nieh, R.; Dickie, M. Field Testing of Outdoor Intrusion Detection Sensors. Proceedings of the 36th International Carnahan Conference on Security Technology, Atlantic City, NJ, USA, 20–24 October 2002; pp. 171–178.
[12]  Ziliani, F.; Cavallaro, A. Evaluation of Multi-Sensor Surveillance Event Detectors. Proceedings of the Institution of Engineering and Technology Conference on Crime and Security, London, UK, 13–14 June 2006; pp. 464–469.
[13]  Mann, S.; Nolan, J.; Wellman, B. Sousveillance: Inventing and using wearable computing devices for data collection in surveillance environments. Surveill. Soc 2003, 1, 331–355.
[14]  Wang, S.W.; Daowei, B. Distributed visual-target-surveillance system in wireless sensor networks. IEEE Trans. Syst. Man Cybern. Part B Cybern 2009, 39, 1134–1146, doi:10.1109/TSMCB.2009.2013196.
[15]  Leung, H.; Chandana, S.; Shuang, W. Distributed sensing based on intelligent sensor networks. IEEE Circuits Syst. Mag 2008, 8, 38–52, doi:10.1109/MCAS.2008.923977.
[16]  Raty, T. High-Level Architecture for a Single Location Surveillance Point. Proceedings of the 3th International Conference on Wireless and Mobile Communications (ICWMC ’07), Guadeloupe, France, 4–9 March 2007; pp. 82–82.
[17]  Raty, T.; Luo, M.; Oikarinen, J.; Nieminen, M. Testing and Validation of a Multi-sensor Distributed Surveillance System. Proceedings of the 7th International Caribbean Conference on Devices, Circuits and Systems (ICCDCS’08), Cancún, México, April 2008; pp. 1–6.
[18]  ACTUAL. Available online: http://www.indracompany.com/en/prensa/actual-indra/edition/2010/9/smart-technology-security-tomorrow-6267 (accessed on 28 February 2012).
[19]  von Neumann, J.; Morgenstern, O. Theory of Games and Economic Behaviour; Princeton University Press: Princeton, NJ, USA; p. 1944.
[20]  Osborne, M.J. An Introduction to Game Theory; Oxford University Press: Oxford, UK, 2004.
[21]  Roughgarden, T. Algorithmic Game Theory; Cambridge University Press: Cambridge, UK; p. 2007.
[22]  Myerson, R.B. Game Theory: Analysis of Conflict; Harvard University Press: Cambridge, MA, USA, 1991.
[23]  Banks, D.L.; Anderson, S. Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example. In Statistical Methods in Counterterrorism; Wilson, A.G., Wilson, G.D., Eds.; Springer-Verlag Inc: New York, NY, USA, 2006; pp. 9–22.
[24]  Ciancarini, P.; Favini, G. Representing Kriegspiel States with Metapositions. Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI’07), Hyderabad, India, 6–12 January 2007; pp. 2450–2455.
[25]  Singh, V.K.; Kankanhalli, M.S. Adversary aware surveillance systems. IEEE Trans. Inf. Forensics Secur 2009, 4, 552–563, doi:10.1109/TIFS.2009.2026459.
[26]  Jiang, W.; Tian, Z.; Zhang, H.; Song, X. A Stochastic Game Theoretic Approach to Attack Prediction and Optimal Active Defense Strategy Decision. Proceedings of the 2008 IEEE International Conference on Networking, Sensing and Control (ICNSC’08), Hainan, China, 6–8 April 2008; pp. 648–653.
[27]  Luo, Y.; Szidarovszky, F.; Al-Nashif, Y.; Hariri, S. A Game Theory Based Risk and Impact Analysis Method for Intrusion Defense Systems. Proceedings of the 2009 IEEE/ACS International Conference on Computer Systems and Applications (AICCSA’09), Rabbat, Morocco, 10–13 May 2009; pp. 975–982.
[28]  Liu, Y.; Man, H.; Comaniciu, C. A Game Theoretic Approach to Efficient Mixed Strategies for Intrusion Detection. Proceedings of the 2006 IEEE International Conference on Communications (ICC'06), Istanbul, Turkey, 11–15 June 2006; 5, pp. 2201–2206.
[29]  Xiaosong, L.; Schwartz, H.M. An Investigation of Guarding a Territory Problem in a Grid World. Proceedings of the American Control Conference (ACC’10), Baltimore, MD, USA, 30 June–2 July 2010; pp. 3204–3210.
[30]  Oberti, F.; Granelli, F.; Regazzoni, C.S. Minimax Based Regulation of Change Detection Threshold in Video-Surveillance Systems. In Multimedia Video-Based Surveillance Systems; Foresti, G.L., M?h?nen, P., Regazzoni, C.S., Eds.; Springer: New York, NY, USA, 2000; Volume 573, pp. 210–223.
[31]  Shapley, L.S. Some Topics in Two-Person Games. Advances in Game Theory; Princeton University Press: Princeton, NJ, USA, 1964; pp. 1–28.
[32]  Rosenthal, R.W. A class of games possessing pure-strategy nash equilibria. Int. J. Game Theory 1973, 2, 65–67, doi:10.1007/BF01737559.
[33]  Harsanyi, J.C. Games with randomly disturbed payoffs: A new rationale for mixed-strategy equilibrium points. Int. J. Game Theory 1973, 2, 1–23, doi:10.1007/BF01737554.
[34]  Juels, A. RFID security and privacy: A research survey. IEEE J. Sel. Areas Commun 2006, 24, 381–394, doi:10.1109/JSAC.2005.861395.
[35]  Warneke, B.; Last, M.; Liebowitz, B.; Pister, K.S.J. Smart dust: Communicating with a cubic-millimeter brett. Computer 2001, 34, 44–51.
[36]  Knuth, D.E.; Moore, R.W. An analysis of alpha-beta pruning. Artif. Intell 1975, 6, 293–326, doi:10.1016/0004-3702(75)90019-3.
[37]  Anglada, M.V. An improved incremental algorithm for constructing restricted delaunay triangulations. Comput. Graph 1997, 21, 215–223, doi:10.1016/S0097-8493(96)00085-4.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133