Intrusion detection using machine learning : past and present
chapter
posted on 2017-12-06, 00:00authored byMohammed Mazid, A B M Shawkat Ali, Kevin Tickle
Intrusion detection has received enormous attention from the beginning of computer network technology. It is the task of detecting attacks against a network and its resources. To detect and counteract any unauthorized activity, it is desirable for network and system administrators to monitor the activities in their network. Over the last few years a number of intrusion detection systems have been developed and are in use for commercial and academic institutes. But still there are some challenges to be solved. This chapter will provide the review, demonstration and future direction on intrusion detection. The authors’ emphasis on Intrusion Detection is various kinds of rule based techniques. The research aims are also to summarize the effectiveness and limitation of intrusion detection technologies in the medical diagnosis, control and model identification in engineering, decision making in marketing and finance, web and text mining, and some other research areas.
Centre for Intelligent and Networked Systems (CINS); Faculty of Arts, Business, Informatics and Education; Institute for Resource Industries and Sustainability (IRIS);