research-article

Eliminating routing protocol anomalies in wireless sensor networks using AI techniques

Authors:

Zorana Banković,

Juan Carlos Vallejo,

Pedro Malagón,

Álvaro Araujo,

José M. MoyaAuthors Info & Claims

AISec '10: Proceedings of the 3rd ACM workshop on Artificial intelligence and security

Pages 8 - 13

https://doi.org/10.1145/1866423.1866426

Published: 08 October 2010 Publication History

Abstract

The specific nature of routing in sensor networks has made possible new sorts of attacks that can have closer insight and effect on the networks packets, the most important being the packet tampering. Routing attacks on the network level are the first step in tampering with the packets. In this work we propose a solution for detecting and eliminating these attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The algorithms use the feature space based on sequences of routing hops that provides ability of detecting wide range of attacks. We further present a flexible way of integrating the solution into targeted sensor network that can easily adapt its computational requirements to the existing network resources. The solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, flexible integration, and high ability in detecting and confining attacks.

References

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Cited By

Khan MAnjum MHassan SJung H(2023)Artificial Intelligence in Mobile and Modern Wireless NetworksAI and Its Convergence With Communication Technologies10.4018/978-1-6684-7702-1.ch003(43-96)Online publication date: 25-Aug-2023
https://doi.org/10.4018/978-1-6684-7702-1.ch003
Usman MMuthukkumarasamy VWu XKhanum SUsman MMuthukkumarasamy VWu XKhanum S(2018)BackgroundMobile Agent-Based Anomaly Detection and Verification System for Smart Home Sensor Networks10.1007/978-981-10-7467-7_2(9-43)Online publication date: 2-Feb-2018
https://doi.org/10.1007/978-981-10-7467-7_2
Usman MMuthukkumarasamy VWu XKhanum SKhan SMauri J(2014)Anomaly Detection in Wireless Sensor NetworksSecurity for Multihop Wireless Networks10.1201/b16754-14(273-304)Online publication date: 25-Mar-2014
https://doi.org/10.1201/b16754-14
Show More Cited By

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Eliminating routing protocol anomalies in wireless sensor networks using AI techniques

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Published In

cover image ACM Conferences

AISec '10: Proceedings of the 3rd ACM workshop on Artificial intelligence and security

October 2010

78 pages

ISBN:9781450300889

DOI:10.1145/1866423

General Chair:
Rachel Greenstadt
Drexel University

Copyright © 2010 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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SIGSAC: ACM Special Interest Group on Security, Audit, and Control

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 October 2010

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CCS '10

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SIGSAC

CCS '10: 17th ACM Conference on Computer and Communications Security 2010

October 8, 2010

Illinois, Chicago, USA

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AISec '10 Paper Acceptance Rate 10 of 15 submissions, 67%;

Overall Acceptance Rate 94 of 231 submissions, 41%

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CCS '25

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ACM SIGSAC Conference on Computer and Communications Security

October 13 - 17, 2025

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Cited By

Khan MAnjum MHassan SJung H(2023)Artificial Intelligence in Mobile and Modern Wireless NetworksAI and Its Convergence With Communication Technologies10.4018/978-1-6684-7702-1.ch003(43-96)Online publication date: 25-Aug-2023
https://doi.org/10.4018/978-1-6684-7702-1.ch003
Usman MMuthukkumarasamy VWu XKhanum SUsman MMuthukkumarasamy VWu XKhanum S(2018)BackgroundMobile Agent-Based Anomaly Detection and Verification System for Smart Home Sensor Networks10.1007/978-981-10-7467-7_2(9-43)Online publication date: 2-Feb-2018
https://doi.org/10.1007/978-981-10-7467-7_2
Usman MMuthukkumarasamy VWu XKhanum SKhan SMauri J(2014)Anomaly Detection in Wireless Sensor NetworksSecurity for Multihop Wireless Networks10.1201/b16754-14(273-304)Online publication date: 25-Mar-2014
https://doi.org/10.1201/b16754-14
Romano LD'Antonio SFormicola VCoppolino L(2012)Protecting the WSN zones of a critical infrastructure via enhanced SIEM technologyProceedings of the 2012 international conference on Computer Safety, Reliability, and Security10.1007/978-3-642-33675-1_20(222-234)Online publication date: 25-Sep-2012
https://dl.acm.org/doi/10.1007/978-3-642-33675-1_20
Fraga DGutiérrez ÁVallejo JCampo ABankovic Z(2011)Improving Social Odometry Robot Networks with Distributed Reputation Systems for Collaborative PurposesSensors10.3390/s11121137211:12(11372-11389)Online publication date: 30-Nov-2011
https://doi.org/10.3390/s111211372
Bankovic ZMoya JVallejo JFraga DMalagon P(2011)Holistic Solution for Confining Insider Attacks in Wireless Sensor Networks Using Reputation Systems Coupled with Clustering TechniquesProceedings of the 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications10.1109/TrustCom.2011.12(61-72)Online publication date: 16-Nov-2011
https://dl.acm.org/doi/10.1109/TrustCom.2011.12

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