We propose a framework for collaborative defense by extending the original distributed intrusion detection model. It contains alert's collector, extractor, analyzer, report's generator, alert warehouse and alert's analysis. Besides, we develop a hybrid approach to share security information like raising the wolf smoke to warn partners. By the security information sharing, the members of CSIRT can obtain the solutions of defense, such as blacklists, detection rules, and security knowledge about alerts. The framework provides a solution to build effective cooperative security teams for academia and industry.We evaluate the feasibility of our framework and track the spreading behaviors of the SQL Slammer Worm. As a result, we can deploy security system more widely and detect the aggressor's behavior more accurately. The alert-based collaborative defense mechanism can help members to evaluate the impact of the threats and take proper actions to mitigate the risk.
Citation:
Wen-Yi Hsin, Shun-Chieh Lin, Shian-Shyong Tseng, "A Study of Alert-Based Collaborative Defense," ispan, pp.148-153, 8th International Symposium on Parallel Architectures,Algorithms and Networks (ISPAN'05), 2005