Evaluating Intrusion Sensitivity Allocation with Support Vector Machine for Collaborative Intrusion Detection

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Author(s)

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Detail(s)

Original languageEnglish
Title of host publicationInformation Security Practice and Experience - 15th International Conference, ISPEC 2019, Proceedings
EditorsSwee-Huay Heng, Javier Lopez
PublisherSpringer
Pages453-463
ISBN (Electronic)9783030343392
ISBN (Print)9783030343385
Publication statusPublished - Nov 2019

Publication series

NameLecture Notes in Computer Science
Volume11879
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title15th International Conference on Information Security Practice and Experience (ISPEC 2019)
PlaceMalaysia
CityKuala Lumpur
Period26 - 28 November 2019

Abstract

The aim of collaborative intrusion detection networks (CIDNs) is to provide better detection performance over a single IDS, through allowing IDS nodes to exchange data or information with each other. Nevertheless, CIDNs may be vulnerable to insider attacks, and there is a great need for deploying appropriate trust management schemes to protect CIDNs in practice. In this work, we advocate the effectiveness of intrusion sensitivity-based trust management model and describe an engineering way to automatically allocate the sensitivity values by using a support vector machine (SVM) classifier. To explore the allocation performance, we compare our classifier with several traditional supervised algorithms in the evaluation. We further investigate the performance of our enhanced trust management scheme in a real network environment under adversarial scenarios, and the experimental results indicate that our approach can be more effective in detecting insider attacks as compared with similar approaches.

Research Area(s)

  • Collaborative intrusion detection, Insider threat, Intrusion sensitivity, Supervised learning, Trust management

Citation Format(s)

Evaluating Intrusion Sensitivity Allocation with Support Vector Machine for Collaborative Intrusion Detection. / Li, Wenjuan; Meng, Weizhi; Kwok, Lam For.

Information Security Practice and Experience - 15th International Conference, ISPEC 2019, Proceedings. ed. / Swee-Huay Heng; Javier Lopez. Springer, 2019. p. 453-463 (Lecture Notes in Computer Science; Vol. 11879).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)