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INCOS '09 Proceedings of the 2009 International Conference on Intelligent Networking and Collaborative Systems
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Low-Overhead Fault Tolerance for High-Throughput Data Processing Systems
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
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Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
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Detection and remediation of security incidents (e.g., attacks, compromised machines, policy violations) is an increasingly important task of system administrators. While numerous tools and techniques are available (e.g., Snort, nmap, netflow), novel attacks and low-grade events may still be hard to detect in a timely manner. In this paper, we present a novel approach for detecting stealthy, low-grade security incidents by utilizing information across a community of organizations (e.g., banking industry, energy generation and distribution industry, governmental organizations in a specific country, etc). The approach uses netflow, a commonly available non-intrusive data source, analyzes communication to/from the community, and alerts the community members when suspicious activity is detected. A community-based detection has the ability to detect incidents that would fall below local detection thresholds while maintaining the number of alerts at a manageable level for each day.