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Computer systems are exposed to an increasing number and type of security threats due to the expanding of Internet in recent years. How to detect network intrusions effectively becomes an important techniques. This paper presents a novel fuzzy class association rule mining method based on Genetic Network Programming (GNP) for detecting network intrusions. GNP is an evolutionary optimization techniques,...
In this paper, a class association rule mining approach based on Genetic Network Programming (GNP) for detecting network intrusion combining misuse detection and anomaly detection is proposed. The proposed approach is an extension of the intrusion detection approach using GNP, so it can detect and distinguish normal, known intrusion and unknown intrusion. The simulation result shows that the detection...
In this paper, we propose a novel method to learn motion patterns and detect anomalies by human trajectory analysis. Human trajectories are various, for example, moving, roaming, pausing, and so on. But, current approaches for the analysis of motion patterns are effective only in understanding simple trajectories. We aim to understand complicated human trajectories with long-term observation. To deal...
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