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Enhancing collaborative intrusion detection networks using intrusion sensitivity in detecting pollution attacks

Enhancing collaborative intrusion detection networks using intrusion sensitivity in detecting... PurposeThis paper aims to propose and evaluate an intrusion sensitivity (IS)-based approach regarding the detection of pollution attacks in collaborative intrusion detection networks (CIDNs) based on the observation that each intrusion detection system may have different levels of sensitivity in detecting specific types of intrusions.Design/methodology/approachIn this work, the authors first introduce their adopted CIDN framework and a newly designed aggregation component, which aims to collect feedback, aggregate alarms and identify important alarms. The authors then describe the details of trust computation and alarm aggregation.FindingsThe evaluation on the simulated pollution attacks indicates that the proposed approach is more effective in detecting malicious nodes and reducing the negative impact on alarm aggregation as compared to similar approaches.Research limitations/implicationsMore efforts can be made in improving the mapping of the satisfaction level, enhancing the allocation, evaluation and update of IS and evaluating the trust models in a large-scale network.Practical implicationsThis work investigates the effect of the proposed IS-based approach in defending against pollution attacks. The results would be of interest for security specialists in deciding whether to implement such a mechanism for enhancing CIDNs.Originality/valueThe experimental results demonstrate that the proposed approach is more effective in decreasing the trust values of malicious nodes and reducing the impact of pollution attacks on the accuracy of alarm aggregation as compare to similar approaches. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information and Computer Security Emerald Publishing

Enhancing collaborative intrusion detection networks using intrusion sensitivity in detecting pollution attacks

Information and Computer Security , Volume 24 (3): 12 – Jul 11, 2016

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References (16)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2056-4961
DOI
10.1108/ICS-12-2014-0077
Publisher site
See Article on Publisher Site

Abstract

PurposeThis paper aims to propose and evaluate an intrusion sensitivity (IS)-based approach regarding the detection of pollution attacks in collaborative intrusion detection networks (CIDNs) based on the observation that each intrusion detection system may have different levels of sensitivity in detecting specific types of intrusions.Design/methodology/approachIn this work, the authors first introduce their adopted CIDN framework and a newly designed aggregation component, which aims to collect feedback, aggregate alarms and identify important alarms. The authors then describe the details of trust computation and alarm aggregation.FindingsThe evaluation on the simulated pollution attacks indicates that the proposed approach is more effective in detecting malicious nodes and reducing the negative impact on alarm aggregation as compared to similar approaches.Research limitations/implicationsMore efforts can be made in improving the mapping of the satisfaction level, enhancing the allocation, evaluation and update of IS and evaluating the trust models in a large-scale network.Practical implicationsThis work investigates the effect of the proposed IS-based approach in defending against pollution attacks. The results would be of interest for security specialists in deciding whether to implement such a mechanism for enhancing CIDNs.Originality/valueThe experimental results demonstrate that the proposed approach is more effective in decreasing the trust values of malicious nodes and reducing the impact of pollution attacks on the accuracy of alarm aggregation as compare to similar approaches.

Journal

Information and Computer SecurityEmerald Publishing

Published: Jul 11, 2016

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