Local outlier factor and stronger one class classifier based hierarchical model for detection of attacks in network intrusion detection dataset

• Published in: Frontiers of Computer Science Vol. 10; no. 4; pp. 755 - 766
• Main Authors: VASUDEVAN, Alampallam Ramaswamy, SELVAKUMAR, Subramanian
• Format: Journal Article
• Language: English
• Published: Beijing Higher Education Press 01.08.2016; Springer Nature B.V
• Subjects: Classifiers; Clustering; Communications traffic; Computer Science; Data analysis; Data mining; Datasets; Deviation; Dirichlet; Dirichlet problem; Discretizer; DP clustering; False alarms; hierarchical model; Intrusion detection systems; LOF; Machine learning; NIDS; one class classifier; Outliers (statistics); Research Article; Supervised learning; Traffic models; 分类器; 因子和; 局部异常因子; 层次模型; 数据集; 监督学习; 网络入侵检测系统; LOF; hierarchical model; one class classifier; DP clustering; NIDS; Discretizer

Identification of attacks by a network intrusion detection system （NIDS） is an important task. In signature or rule based detection, the previously encountered attacks are modded, and signatures/rules are extracted. These rules are used to detect such attacks in future, but in anomaly or outlier det...