Collaborative RFID intrusion detection with an artificial immune system

Journal of Intelligent Information Systems

Volumn 36, Issue 1, 2011, Pages 1-26

  Yang, Haidong ^a   Guo, Jianhua ^b   Deng, Feiqi ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b GUANGDONG POLYTECHNIC NORMAL UNIVERSITY   (China)

Author keywords

Artificial immune system (AIS); Collaborative intrusion detection; Immune based clustering; Negative selection; Radio Frequency IDentification (RFID)

Indexed keywords

ADAPTIVE DETECTORS; ARTIFICIAL IMMUNE SYSTEM; BIOLOGICAL IMMUNE SYSTEM; COLLABORATIVE INTRUSION DETECTION; DANGER SIGNALS; DATA MODELS; DETECTION RATES; FALSE DETECTIONS; IMMUNE BASED CLUSTERING; IMMUNE CELLS; INTRUSION DETECTION METHOD; NEGATIVE SELECTION; NEGATIVE SELECTION ALGORITHM; PHYSICAL PROTECTION; RFID ATTACKS; RFID SYSTEMS; SIMULATION RESULT; TECHNICAL STANDARDS;

ADAPTIVE ALGORITHMS; ANTIGENS; AUTHENTICATION; CLUSTERING ALGORITHMS; CRYPTOGRAPHY; DETECTORS; IMMUNOLOGY; INTRUSION DETECTION; RADIO WAVES; SIGNAL DETECTION;

RADIO FREQUENCY IDENTIFICATION (RFID);

EID: 79951556944     PISSN: 09259902     EISSN: 15737675     Source Type: Journal    
DOI: 10.1007/s10844-010-0118-3     Document Type: Article

References (29)

1. Ahson, S.; Ilyas, M. (2008). RFID handbook: Applications, technology, security, and privacy. Boca Raton: CRC.
2. Aickelin, U.; Cayzer, S. (2002). The danger theory and its applications to artificial immune systems. In Proceedings of the first international conference on artificial immune systems (pp. 141-148).
3. Aickelin, U.; Bentley, P.; Cayzer, S.; Kim, J.; McLeod, J. (2003). Danger theory: The link between AIS and IDS. Report LPL-2003-138, HP Laboratories Bristol 2003. Available at www.hpl.hp.com/techreports/2003/HPL-2003-138.pdf.
4. J Ayoade 2007 Privacy and RFID systems: Roadmap to solving security and privacy concerns in RFID systems Comput (Pubitemid 350026134)
5. D'haeseleer, P.; Forrest, S.; Helman, P. (1996). An immunological approach to change detection: Algorithms, analysis and implications. In Proceedings of IEEE symposium on security and privacy (pp. 110-119).
6. De Castro, L.; Von Zuben, F. (2000). An evolutionary immune network for data clustering. In Proceedings of the 6th Brazilian symposium on neural networks (pp. 84-89). Los Alamitos: IEEE Computer Society.
7. EPCTM (2007). EPCTM radio frequency identity protocols class-1 generation-2 UHF RFID protoco1 for communications at 860M Hz-960MHz version 1.1.0. EPCglobal.
8. Forrest, S.; Hofmeyr, S. (2000). Immunology as information processing. In L. A. Segel, I. R. Cohen (Eds.), Design principles for immune system other distributed autonomous systems (pp. 361-387). Oxford: Oxford University Press.
9. Forrest, S.; Longstaff, T.; Hofmeyr, S.; Somayaji, A. (1996). A sense of self for unix process. In Proceedings of the IEEE symposium on security and privacy (pp. 120-128). Los Alamitos: IEEE Computer Society.
10. Forrest, S.; Perelson, A.; Allen, L.; Cherukuri, R. (1994). Self-nonself discrimination in a computer. In Proceedings of the IEEE symposium on security and privacy (pp. 201-212). Los Alamitos: IEEE Computer Society.
11. H Fu X Li 2008 Double-signal based immune intrusion detection model inspired by danger theory Computer Engineering and Applications 44 14 113 117 2530474 (in Chinese)
12. J Guo H Yang F Deng 2008 Intrusion detection model for RFID system based on immune network Journal of Computer Applications 28 10 2481 2484 1181.68025 10.3724/SP.J.1087.2008.02481 (in Chinese)
13. Hofmeyr, S. (2000). An interpretative introduction to the immune system. Department of Computer Science, University of New Mexico. Available at http://www.cs.unm.edu/~steveah/imm-overview-new.pdf.
14. S Hofmeyr S Forrest 2000 Architecture for an artificial immune system Evolutionary Computation 8 4 443 473 10.1162/106365600568257
15. Z Hong L Wu Y Wang 2008 Worm containment model based on negative selection Computer Engineering 34 7 126 128 (in Chinese)
16. A Juels 2006 RFID security and privacy: A research survey IEEE Journal on Selected Areas in Communications 24 2 381 395 10.1109/JSAC.2005.861395 2197471 (Pubitemid 43269757)
17. J Li X Gao L Jiao 2004 A novel clustering method with network structure based on clonal algorithm ACTA Electronica Sinica 32 7 1195 1199 (in Chinese)
18. T Lunt 1993 A survey of intrusion detection techniques Computers Security 12 1 405 418 10.1016/0167-4048(93)90029-5 (Pubitemid 23707839)
19. P Matzinger 1994 Tolerance, danger and the extended family Annual Review of Immunology 12 991 1045
20. L Mirowski J Hartnett 2007 Deckard: A system to detect change of RFID tag ownership International Journal of Computer Science and Network Security 7 7 89 98
21. Ohkubo, M.; Suzuki, K.; Kinoshita, S. (2004). Hash-chain based forward-secure privacy protection scheme for low-cost RFID. In Proceedings of the 2004 symposium on cryptography and information security (SCIS2004) (pp. 719-724). Sendai: SCIS.
22. Rivest, R. (1992). The MD5 message-digest algorithm. MIT Laboratory for Computer Science and RSA Data Security, Inc. Available at http://www.ietf.org/ rfc/rfc1321.txt.
23. P Rotter 2008 A framework for assessing RFID system security and privacy risks IEEE Pervasive Computing 7 2 70 77 10.1109/MPRV.2008.22 (Pubitemid 351575124)
24. SE Sarma SA Weis D Wengels 2003 Radio-frequency identification: Secure risks and challenges RSA Laboratories Cryptobytes 6 1 2 9
25. Thamilarasu, G.; Sridhar, R. (2008). Intrusion detection in RFID systems. In Military communications conference (pp. 1-7). San Diego: IEEE.
26. Weis, S. A.; Sarma, S. E.; Rivest, R. L.; et al. (2004). Security and privacy aspects of low-cost radio frequency identification systems. In Proceedings of the 1st international conference on security in pervasive computing (pp. 201-212). Berlin: Springer.
27. Williamson, M. (2002). Biologically inspired approaches to computer security. Report LPL-2002-131, HP Laboratories Bristol 2002. Available at http://www.hpl.hp.com/techreports/2002/HPL-2002-131.pdf.
28. H Xu C Xu X Cheng Z Peng 2009 Research and design of adaptive intrusion prevention system for co-stimulated by danger signals Computer Engineering 35 2 172 174 (in Chinese)
29. Q Zhang Y Qian B Xu T Gao K Xie 2007 Negative-selection algorithm of mutation search in self space to train detector Journal of Computer Applications 27 3 627 629 (in Chinese)