Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Abstract—In network intrusion detection research, one popular strategy for finding attacks is monitoring a network’s activity for anomalies: deviations from profiles of norma...
The Snort intrusion detection system is a widely used and well-regarded open sourcesystem used for the detection of malicious activity in conventional wired networks. Recently, so...
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
Intrusion detection is an active research field in the development of reliable web-based information systems, where many artificial intelligence techniques are exploited to fit th...