The accuracy of detecting an intrusion within a network of intrusion detection systems (IDSes) depends on the efficiency of collaboration between member IDSes. The security itself within this network is an additional concern that needs to be addressed. In this paper, we present a trust-based framework for secure and effective collaboration within an intrusion detection network (IDN). In particular, we define a trust model that allows each IDS to evaluate the trustworthiness of others based on personal experience. We prove the correctness of our approach in protecting the IDN. Additionally, experimental results demonstrate that our system yields a significant improvement in detecting intrusions. The trust model further improves the robustness of the collaborative system against malicious attacks. © 2008 Springer-Verlag.
CITATION STYLE
Fung, C. J., Baysal, O., Zhang, J., Aib, I., & Boutaba, R. (2008). Trust management for host-based collaborative intrusion detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5273 LNCS, pp. 109–122). Springer Verlag. https://doi.org/10.1007/978-3-540-87353-2_9
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