Communications of the ACM
Code-Red: a case study on the spread and victims of an internet worm
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Indra: A peer-to-peer approach to network intrusion detection and prevention
WETICE '03 Proceedings of the Twelfth International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises
Trusting advice from other buyers in e-marketplaces: the problem of unfair ratings
ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
A Trust-Aware, P2P-Based Overlay for Intrusion Detection
DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
Towards scalable and robust distributed intrusion alert fusion with good load balancing
Proceedings of the 2006 SIGCOMM workshop on Large-scale attack defense
SMURFEN: a system framework for rule sharing collaborative intrusion detection
Proceedings of the 7th International Conference on Network and Services Management
Game theory meets network security and privacy
ACM Computing Surveys (CSUR)
| Hi-index | 0.00 |
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.