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Book chapter ยท Conference paper

Towards Securing Challenge-Based Collaborative Intrusion Detection Networks via Message Verification

From

City University of Hong Kong1

Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Cyber Security, Department of Applied Mathematics and Computer Science, Technical University of Denmark3

Guangzhou University4

University of Surrey5

With the increasing number of Internet-of-Things (IoT) devices, intrusion detection systems (IDSs) have been widely deployed in a distributed or collaborative setting, in which a collaborative intrusion detection network (CIDN) improves the detection accuracy of a single IDS by enabling IDS nodes to exchange useful information with each other.

To protect CIDNs against insider attacks, challenge-based trust mechanisms are one promising solution to detect malicious nodes through sending challenges. However, several studies have revealed that this kind of mechanism is still vulnerable to some advanced insider attacks like passive message fingerprint attack (PMFA).

Motivated by this observation, in this work, we focus on enhancing the security of challenge-based CIDNs and propose a compact but efficient message verification approach to defeat such insider attack by inserting a verifying alarm into each normal request. In the evaluation, we investigate the attack performance under both simulated and real network environments.

Experimental results demonstrate that our approach can identify malicious nodes under PMFA and decrease their trust values in a quick manner.

Language: English
Publisher: Springer International Publishing
Year: 2018
Pages: 313-328
Proceedings: 14th International Conference on Information Security Practice and Experience
Series: Lecture Notes in Computer Science
Journal subtitle: 14th International Conference, Ispec 2018, Tokyo, Japan, September 25-27, 2018, Proceedings
ISBN: 3319998064 , 3319998072 , 9783319998060 and 9783319998077
ISSN: 03029743
Types: Book chapter and Conference paper
DOI: 10.1007/978-3-319-99807-7_19
ORCIDs: Meng, Weizhi

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