Practical Bayesian Poisoning Attacks on Challenge-Based Collaborative Intrusion Detection Networks

Weizhi Meng, Wenjuan Li, Lijun Jiang, Kim Kwang Raymond Choo, Chunhua Su

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

As adversarial techniques constantly evolve to circumvent existing security measures, an isolated, stand-alone intrusion detection system (IDS) is unlikely to be efficient or effective. Hence, there has been a trend towards developing collaborative intrusion detection networks (CIDNs), where IDS nodes collaborate and communicate with each other. Such a distributed ecosystem can achieve improved detection accuracy, particularly for detecting emerging threats in a timely fashion (before the threat becomes common knowledge). However, there are inherent limitations due to malicious insiders who can seek to compromise and poison the ecosystem. A potential mitigation strategy is to introduce a challenge-based trust mechanism, in order to identify and penalize misbehaving nodes by evaluating the satisfaction between challenges and responses. While this mechanism has been shown to be robust against common insider attacks, it may still be vulnerable to advanced insider attacks in a real-world deployment. Therefore, in this paper, we develop a collusion attack, hereafter referred to as Bayesian Poisoning Attack, which enables a malicious node to model received messages and to craft a malicious response to those messages whose aggregated appearance probability of normal requests is above the defined threshold. In the evaluation, we explore the attack performance under both simulated and real network environments. Experimental results demonstrate that the malicious nodes under our attack can successfully craft and send untruthful feedback while maintaining their trust values.

Original languageEnglish
Title of host publicationComputer Security – ESORICS 2019 - 24th European Symposium on Research in Computer Security, Proceedings
EditorsKazue Sako, Steve Schneider, Peter Y.A. Ryan
PublisherSpringer
Pages493-511
Number of pages19
ISBN (Print)9783030299583
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event24th European Symposium on Research in Computer Security, ESORICS 2019 - Luxembourg, Luxembourg
Duration: 23 Sep 201927 Sep 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11735 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th European Symposium on Research in Computer Security, ESORICS 2019
Country/TerritoryLuxembourg
CityLuxembourg
Period23/09/1927/09/19

Keywords

  • Bayesian Poisoning Attack
  • Challenge-based trust mechanism
  • Collaborative network
  • Insider threat
  • Intrusion detection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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