research-article

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

Authors:

Muddassar FarooqAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 63 - 70

https://doi.org/10.1145/1389095.1389105

Published: 12 July 2008 Publication History

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]

L. N. de Castro and J. Timmis. Artificial immune systems: a new computational intelligence approach. Springer, 2002.

Digital Library

[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.

Digital Library

[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, and David B. Johnson. Ariadne: A secure on-demand routing protocol for ad hoc networks. Wireless Networks, 11(1-2):21--38, 2005.

Digital Library

[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.

Digital Library

[12]

N. Mazhar and M. Farooq. Vulnerability analysis and security framework (beesec) for nature inspired manet routing protocols. In Proceedings of GECCO-2007, pages 102--109, July, 2007.

Digital Library

[13]

C. Perkins and E. Royer. Ad-hoc on-demand distance vector routing. In Proceedings of 2nd IEEE Workshop on Mobile Computing Systems and Applications, pages 90--100, Feb 1999.

Digital Library

[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.

Digital Library

[17]

H.F. Wedde, M. Farooq, T. Pannenbaecker, B. Vogel, C. Mueller, J. Meth, and R. Jeruschkat. Beeadhoc: an energy efficient routing algorithm for mobile ad hoc networks inspired by bee behavior. In GECCO, pages 153--160, 2005.

Digital Library

[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.

Digital Library

[19]

Manel Guerrero Zapata. Secure ad hoc on-demand distance vector (saodv) routing. Internet-Draft, draft-guerrero-manetsaodv-05.txt, February, 2005.

Cited By

Jim LIslam NGregory M(2022)Enhanced MANET security using artificial immune system based danger theory to detect selfish nodesComputers and Security10.1016/j.cose.2021.102538113:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.cose.2021.102538
Aldhaheri SAlghazzawi DCheng LAlzahrani BAl-Barakati A(2020)DeepDCA: Novel Network-Based Detection of IoT Attacks Using Artificial Immune SystemApplied Sciences10.3390/app1006190910:6(1909)Online publication date: 11-Mar-2020
https://doi.org/10.3390/app10061909
Aldhaheri SAlghazzawi DCheng LBarnawi AAlzahrani B(2020)Artificial Immune Systems approaches to secure the internet of thingsJournal of Network and Computer Applications10.1016/j.jnca.2020.102537157:COnline publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1016/j.jnca.2020.102537
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Index Terms

A sense of danger: dendritic cells inspired artificial immune system for manet security
1. Hardware
  1. Communication hardware, interfaces and storage
2. Networks
  1. Network protocols
    1. Network layer protocols
      1. Routing protocols
    2. Protocol correctness
      1. Protocol testing and verification

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 July 2008

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GECCO08

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Jim LIslam NGregory M(2022)Enhanced MANET security using artificial immune system based danger theory to detect selfish nodesComputers and Security10.1016/j.cose.2021.102538113:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.cose.2021.102538
Aldhaheri SAlghazzawi DCheng LAlzahrani BAl-Barakati A(2020)DeepDCA: Novel Network-Based Detection of IoT Attacks Using Artificial Immune SystemApplied Sciences10.3390/app1006190910:6(1909)Online publication date: 11-Mar-2020
https://doi.org/10.3390/app10061909
Aldhaheri SAlghazzawi DCheng LBarnawi AAlzahrani B(2020)Artificial Immune Systems approaches to secure the internet of thingsJournal of Network and Computer Applications10.1016/j.jnca.2020.102537157:COnline publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1016/j.jnca.2020.102537
Raja KNatarajan I(2017)Enhanced Negative Selection Algorithm for Malicious Node Detection in MANET2017 Ninth International Conference on Advanced Computing (ICoAC)10.1109/ICoAC.2017.8441315(293-300)Online publication date: Dec-2017
https://doi.org/10.1109/ICoAC.2017.8441315
Rajasekhar ALynn NDas SSuganthan P(2017)Computing with the collective intelligence of honey bees – A surveySwarm and Evolutionary Computation10.1016/j.swevo.2016.06.00132(25-48)Online publication date: Feb-2017
https://doi.org/10.1016/j.swevo.2016.06.001
Jim LGregory M(2016)A Review of Artificial Immune System Based Security Frameworks for MANETInternational Journal of Communications, Network and System Sciences10.4236/ijcns.2016.9100109:01(1-18)Online publication date: 2016
https://doi.org/10.4236/ijcns.2016.91001
Leonov A(2016)Application of bee colony algorithm for FANET routing2016 17th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM)10.1109/EDM.2016.7538709(124-132)Online publication date: Jun-2016
https://doi.org/10.1109/EDM.2016.7538709
Jim LGregory M(2016)Packet Storage Time attack - a novel routing attack in Mobile Ad hoc Networks2016 26th International Telecommunication Networks and Applications Conference (ITNAC)10.1109/ATNAC.2016.7878795(127-132)Online publication date: Dec-2016
https://doi.org/10.1109/ATNAC.2016.7878795
Elizabeth Jim LGregory M(2015)State analysis of Mobile Ad Hoc Network nodesProceedings of the 2015 International Telecommunication Networks and Applications Conference (ITNAC)10.1109/ATNAC.2015.7366832(314-319)Online publication date: 18-Nov-2015
https://dl.acm.org/doi/10.1109/ATNAC.2015.7366832
Mazhar NFarooq M(2011)A hybrid artificial immune system (AIS) model for power aware secure Mobile Ad Hoc Networks (MANETs) routing protocolsApplied Soft Computing10.1016/j.asoc.2011.03.02111:8(5695-5714)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.asoc.2011.03.021
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