A unit-circle classification algorithm to characterize back attack and normal traffic for intrusion detection
作者： Shan Suthaharan
关键词: Data mining 、 Computer science 、 Intrusion detection system 、 Representation (mathematics) 、 Unit circle 、 Standard score 、 Class (biology) 、 Feature (computer vision) 、 Network security 、 Algorithm 、 Anomaly-based intrusion detection system
摘要: A simple, yet effective, unit-circle algorithm for an intrusion detection system is presented. It defines normal and abnormal classes using the normalized “standard scores” of traffic data with a novel representation. In this approach, feature values are first standardized to reduce statistical dependencies local structural variations within class then isolate inaccuracies between classes. constructed two selected features. The reveals that back attack in NSL-KDD datasets fall inside respectively. Hence we have robust definitions activities computer network based on dataset.
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