Detecting Insider Attacks Using Non-negative Matriz Factorization

摘要：

It is a fact that vast majority of attention is given to protecting against external threats, which are considered more dangerous. However, some industrial surveys have indicated they have had attacks reported internally. Insider Attacks are an unusual type of threat which are also serious and very common. Unlike an external intruder, in the case of internal attacks, the intruder is someone who has been entrusted with authorized access to the network. This paper presents a Non-negative Matrix Factorization approach to detect inside attacks. Comparisons with other established pattern recognition techniques reveal that the Non-negative Matrix Factorization approach could be also an ideal candidate to detect internal threats.

关键词： non-negative matriz factorization intrusion detection

作者: Jan Plato(s) V(a)clav Sn(as)el Pavel Kr(o)mer Ajith Abraham

作者单位: Department of Computer Science VSB-Technical University of Ostrava Ostrava,Czech Republic Machine Intelligence Research Labs (MIR Labs),USA

会议类型: 国际会议

会议名称: The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

会议地点: 西安

会议语种:英文

页码: 693-696

在线出版日期: 2009-08-18（万方平台首次上网日期，不代表论文的发表时间）