Using learned data patterns to detect malicious nodes in sensor networks

Partha Mukherjee, Sandip Sen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

As sensor network applications often involve remote, distributed monitoring of inaccessible and hostile locations, they are vulnerable to both physical and electronic security breaches. The sensor nodes, once compromised, can send erroneous data to the base station, thereby possibly compromising network effectiveness. We consider sensor nodes organized in a hierarchy where the non-leaf nodes serve as the aggregators of the data values sensed at the leaf level and the Base Station corresponds to the root node of the hierarchy. To detect compromised nodes, we use neural network based learning techniques where the nets are used to predict the sensed data at any node given the data reported by its neighbors in the hierarchy. The differences between the predicted and the reported values is used to update the reputation of any given node. We compare a Q-learning schemes with the Beta reputation management approach for their responsiveness to compromised nodes. We evaluate the robustness of our detection schemes by varying the members of compromised nodes, patterns in sensed data, etc.

Original languageEnglish (US)
Title of host publicationDistributed Computing and Networking - 9th International Conference, ICDCN 2008, Proceedings
PublisherSpringer Verlag
Pages339-344
Number of pages6
ISBN (Print)3540774432, 9783540774433
DOIs
StatePublished - Jan 1 2008
Event9th International Conference on Distributed Computing and Networking, ICDCN 2008 - Kolkata, India
Duration: Jan 5 2008Jan 8 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4904 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Distributed Computing and Networking, ICDCN 2008
CountryIndia
CityKolkata
Period1/5/081/8/08

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Mukherjee, P., & Sen, S. (2008). Using learned data patterns to detect malicious nodes in sensor networks. In Distributed Computing and Networking - 9th International Conference, ICDCN 2008, Proceedings (pp. 339-344). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4904 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-77444-0_35