| Publisher | University of Melbourne | ||
|---|---|---|---|
| Format | 408.6KB PDF | Date added | 29 Nov 2005 |
| Topics | Network Design, Security Tools, Intrusion Detection Systems | ||
| Downloads | 9 | ||
Many types of network intrusions occur in multiple networks simultaneously, for example, scanning, worms, and denial-of-service attacks. Most of the current intrusion detection systems work in isolation to detect these attacks. Past research has shown that collaboration between these networks to share suspicious information is an effective way to detect intrusion. However, there are some challenges associated with the idea of collaborative detection, such as scalability and avoidance of a central point of failure. This paper proposes a peer-to-peer approach for collaborative intrusion detection to address these challenges. This solution proposes secure data sharing between participants from different organizations using a content based peer-to-peer publish/subscribe mechanism. The proposed scheme improves scalability, while avoiding a central point of failure.
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