A Blockchain Approach to Identifying Compromised Nodes in Collaborative Intrusion Detection Systems

Chandralekha Yenugunti, Stephen S. Yau

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

Abstract

Large organizations have multiple networks that are subject to attacks which can be detected by Intrusion Detection Systems. Collaborative Intrusion Detection Systems (CIDS) are used for efficient detection of distributed attacks in large networks by having a global view of the attacks in the networks. However, CIDS are vulnerable to various attacks, which compromise some of the nodes of CIDS. The major challenge caused by these attacks on CIDS is due to insider attacks. These insider attacks decrease the mutual trust among the nodes in CIDS, which is required for sharing critical and sensitive alert data. The compromised nodes will further decrease the accuracy of CIDS by generating false positives and false negatives of the traffic classifications. In this paper, an approach based on trust score system is presented to identify and suspend the compromised nodes in CIDS to improve the trust among the nodes for collaboration. This approach is implemented on a private blockchain because private blockchain provides the features to satisfy the accountability, integrity and privacy requirements of CIDS.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages87-93
Number of pages7
ISBN (Electronic)9781728166094
DOIs
StatePublished - Aug 2020
Event18th IEEE International Conference on Dependable, Autonomic and Secure Computing, 18th IEEE International Conference on Pervasive Intelligence and Computing, 6th IEEE International Conference on Cloud and Big Data Computing and 5th IEEE Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020 - Virtual, Calgary, Canada
Duration: Aug 17 2020Aug 24 2020

Publication series

NameProceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020

Conference

Conference18th IEEE International Conference on Dependable, Autonomic and Secure Computing, 18th IEEE International Conference on Pervasive Intelligence and Computing, 6th IEEE International Conference on Cloud and Big Data Computing and 5th IEEE Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
Country/TerritoryCanada
CityVirtual, Calgary
Period8/17/208/24/20

Keywords

  • collaborative intrusion detection systems
  • insider attacks
  • private blockchain
  • trust score

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Science (miscellaneous)
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Modeling and Simulation

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