Robust sybil detection for MANETs

Athichart Tangpong, George Kesidis, Hung Yuan Hsu, Ali Hurson

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

21 Scopus citations

Abstract

In this research, we propose a robust Sybil attack detection framework for MANETs based on cooperative monitoring of network activities.We do not require designated and honest monitors to perform the Sybil attack detection. Each mobile node in the network observes packets passing through it and periodically exchanges its observations in order to determine the presence of an attack. Malicious nodes fabricating false observations will be detected and rendered ineffective. Our framework requires no centralized authority and, thus, is scalable in expanding network size. Privacy of each mobile node is also a consideration of our framework. Our preliminary experimental results yield above 80% accuracy (true positives) and about 10% error rate (false positives).

Original languageEnglish (US)
Title of host publication2009 Proceedings of 18th International Conference on Computer Communications and Networks, ICCCN 2009
DOIs
StatePublished - Nov 12 2009
Event2009 18th International Conference on Computer Communications and Networks, ICCCN 2009 - San Francisco, CA, United States
Duration: Aug 3 2009Aug 6 2009

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
ISSN (Print)1095-2055

Other

Other2009 18th International Conference on Computer Communications and Networks, ICCCN 2009
CountryUnited States
CitySan Francisco, CA
Period8/3/098/6/09

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

Cite this

Tangpong, A., Kesidis, G., Hsu, H. Y., & Hurson, A. (2009). Robust sybil detection for MANETs. In 2009 Proceedings of 18th International Conference on Computer Communications and Networks, ICCCN 2009 [5235387] (Proceedings - International Conference on Computer Communications and Networks, ICCCN). https://doi.org/10.1109/ICCCN.2009.5235387