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The accuracy of detecting intrusions within a Collaborative Intrusion Detection Network (CIDN) depends on the efficiency of collaboration between peer Intrusion Detection Systems (IDSes) as well as the security itself of the CIDN. In this paper, we propose Dirichlet-based trust management to measure the level of trust among IDSes according to their mutual experience. An acquaintance management algorithm is also proposed to allow each IDS to manage its acquaintances according to their trustworthiness. Our approach achieves strong scalability properties and is robust against common insider threats, resulting in an effective CIDN. We evaluate our approach based on a simulated CIDN, demonstrating its improved robustness, efficiency and scalability for collaborative intrusion detection in comparison with other existing models.