Swarm-Based Knowledge Discovery for Intrusion Behavior Discovering
作者： Xiaohui Cui , Justin Beaver , Thomas Potok
关键词: Security management 、 Intrusion detection system 、 Knowledge extraction 、 Data visualization 、 Visualization 、 Swarm behaviour 、 Pattern recognition (psychology) 、 Artificial intelligence 、 Exploit 、 Machine learning 、 Computer science
摘要: In this research, we developed a technique, the Swarm-based Visual Data Mining approach (SVDM), that will help user to gain insight into Intrusion Detection System (IDS) alert event data stream, come up with new hypothesis, and verify hypothesis via interaction between human system. This novel malicious detection system can efficiently security officer detect anomaly behaviors of in high dimensional time dependent state spaces. system's visual representations exploit being's innate ability recognize patterns utilize manager understand relationships seemingly discrete breaches.
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ieeecomputersociety.org参考文章(16)
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