A sense of danger: dendritic cells inspired artificial immune system for manet security

ABSTRACT

AIS-based intrusion detection systems classically utilize the paradigm of self/non-self discrimination. In this approach, an algorithm learns self during a learning phase, therefore, such algorithms do not have the ability to cope with scenarios in which self is continuously changing with time. This situation is encountered once malicious nodes are to be detected in a Mobile Ad Hoc Network (MANET). Consequently, it becomes a challenge to differentiate a valid route change due to mobility from an illegal one due to tampering of routing information by malicious nodes. In this paper, we propose a dendritic cell based distributed misbehavior detection system, BeeAIS-DC, for a Bio/Nature inspired MANET routing protocol, BeeAdHoc. Our proposed system inspires from the danger theory and models the function and behavior of dendritic cells to detect the presence or absence of danger and provides a tolerogenic or immunogenic response. The proposed detection system is implemented in a well-known ns-2 simulator. Our results indicate that our detection system not only enables BeeAIS-DC to dynamically adapt its detector set to cater for a changing self due to mobility of nodes, but also is robust enough to provide significantly smaller false positives as compared to self/non-self based AIS. Moreover, the danger theory related overhead of BeeAIS-DC is minimal, and as a result, it does not degrade traditional performance metrics of BeeAdHoc. This behavior is vital for battery/bandwidth constrained mobile nodes.

REFERENCES

• 1: U. Aickelin, P. Bentley, S. Cayzer, J. Kim, and J. McLeod. Danger theory: The link between ais and ids. In Proceedings of the ICARIS-2003, LNCS 2728, pages 147--155, 2003.
• 2: U. Aickelin and S. Cayzer. The danger theory and its applications to artificial immune systems. In Proceedings of the ICARIS-2002, pages 141--148, 2002.
• 3: U. Aickelin, J. Greensmith, and J. Twycross. Immune system approaches to intrusion detection - a review. In Proceedings of the ICARIS-2004, LNCS 3239, pages 316--329, 2004.
• 4: G. Di Caro, F. Ducatelle, and L.M. Gambardella. Anthocnet: An adaptive nature inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications, 16(2):443--455, 2005.
• 5: Leandro R. de Castro , Jonathan Timmis, Artificial Immune Systems: A New Computational Intelligence Paradigm, Springer-Verlag New York, Inc., Secaucus, NJ, 2002
• 6: J. Greensmith, U. Aickelin, and S. Cayzer. Introducing dendritic cells as a novel immune-inspired algorithm for anomaly detection. In Proceedings of the ICARIS-2005, LNCS 3627, pages 153--167, 2005.
• 7: J. Greensmith, J. Twycross, and U. Aickelin. Dendritic cells for anomaly detection. In Proceedings of the CEC, pages 664--671, 2006.
• 8: Yih-Chun Hu , Adrian Perrig , David B. Johnson, Ariadne: a secure on-demand routing protocol for ad hoc networks, Wireless Networks, v.11 n.1-2, p.21-38, January 2005 [doi>10.1007/s11276-004-4744-y]
• 9: David B Johnson and David A Maltz. Dynamic source routing in ad hoc wireless networks. In Imielinski and Korth, editors, Mobile Computing, pages 153--181. 1996.
• 10: P. Matzinger. Tolerance, danger, and the extended family. Annual Review of Immunology, 12:991--1045, 1994.
• 11: N. Mazhar and M. Farooq. Beeais: Artificial immune system security for nature inspired, manet routing protocol, beeadhoc. In Proceedings of ICARIS-2007, LNCS 4628, pages 370--381, Aug, 2007.
• 12: Nauman Mazhar , Muddassar Farooq, Vulnerability analysis and security framework (BeeSec) for nature inspired MANET routing protocols, Proceedings of the 9th annual conference on Genetic and evolutionary computation, July 07-11, 2007, London, England [doi>10.1145/1276958.1276973]
• 13: Charles E. Perkins , Elizabeth M. Royer, Ad-hoc On-Demand Distance Vector Routing, Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications, p.90, February 25-26, 1999
• 14: Danger Project. http://www.dangertheory.com.
• 15: M. Roth and S.Wicker. Termite: Ad-hoc networking with stigmergy. In Proceedings of IEEE GLOBE-COM, Dec 2003.
• 16: S. Sarafijanovic and J.Y. Le Boudec. An artificial immune system approach with secondary response for misbehavior detection in mobile ad-hoc networks. IEEE Transactions on Neural Networks, 16(5), Sep 2005.
• 17: Horst F. Wedde , Muddassar Farooq , Thorsten Pannenbaecker , Bjoern Vogel , Christian Mueller , Johannes Meth , Rene Jeruschkat, BeeAdHoc: an energy efficient routing algorithm for mobile ad hoc networks inspired by bee behavior, Proceedings of the 2005 conference on Genetic and evolutionary computation, June 25-29, 2005, Washington DC, USA [doi>10.1145/1068009.1068034]
• 18: H.F. Wedde, C. Timm, and M. Farooq. Beehiveais: A simple, efficient, scalable and secure routing framework inspired by artificial immune systems. In PPSN, pages 623--632, 2006.
• 19: Manel Guerrero Zapata. Secure ad hoc on-demand distance vector (saodv) routing. Internet-Draft, draft-guerrero-manetsaodv-05.txt, February, 2005.

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.0 General
          Subjects: Security and protection (e.g., firewalls)

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.0 General
          Subjects: Data communications
      C.2.2 Network Protocols
          Subjects: Protocol verification; Routing protocols

General Terms:
Algorithms, Design, Performance, Security

Keywords:
artificial immune systems, dendritic cells, misbehavior detection, mobile ad hoc networks, self organization