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...
Web-based vulnerabilities represent a substantial portion of the security exposures of computer networks. In order to detect known web-based attacks, misuse detection systems are ...
It is generally agreed that two key points always attract special concerns during the modelling of anomaly-based intrusion detection. One is the techniques about discerning two cl...
A genetic algorithm is combined with two variants of the modularity (Q) network analysis metric to examine a substantial amount fisheries catch data. The data set produces one of t...
Garnett Carl Wilson, Simon Harding, Orland Hoeber,...
Traditional intrusion detection systems (IDS) detect attacks by comparing current behavior to signatures of known attacks. One main drawback is the inability of detecting new atta...