Abstract
Cyber attacks are greatly expanding in both size and complexity. To handle this issue, research has been focused on collaborative intrusion detection networks (CIDNs), which can improve the detection accuracy of a single IDS by allowing various nodes to communicate with each other. While such collaborative system or network is vulnerable to insider attacks, which can significantly reduce the advantages of a detector. To protect CIDNs against insider attacks, one potential way is to enhance the trust evaluation among IDS nodes, i.e., by emphasizing the impact of expert nodes. In this work, we adopt the notion of intrusion sensitivity that assigns different values of detection capability relating to particular attacks, and evaluate its impact on defending against a special On-Off attack (SOOA). In the evaluation, we investigate the impact of intrusion sensitivity in a simulated CIDN environment, and experimental results demonstrate that the use of intrusion sensitivity can help enhance the security of CIDNs under adversarial scenarios, like SOOA.
Original language | English |
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Title of host publication | Proceedings of 18th International Conference on Algorithms and Architectures for Parallel Processing |
Publisher | Springer |
Publication date | 1 Jan 2018 |
Pages | 481-494 |
ISBN (Print) | 9783030050627 |
DOIs | |
Publication status | Published - 1 Jan 2018 |
Event | 18th International Conference on Algorithms and Architectures for Parallel Processing - Guangzhou, China Duration: 15 Nov 2018 → 17 Nov 2018 Conference number: 18 |
Conference
Conference | 18th International Conference on Algorithms and Architectures for Parallel Processing |
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Number | 18 |
Country/Territory | China |
City | Guangzhou |
Period | 15/11/2018 → 17/11/2018 |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11337 |
ISSN | 0302-9743 |
Keywords
- Challenge-based trust mechanism
- Collaborative network
- Insider attack
- Intrusion detection
- Intrusion sensitivity