Australian Digital Forensics Conference
Document Type
Conference Proceeding
Publisher
SRI Security Research Institute, Edith Cowan University, Perth, Western Australia
Abstract
Cyber-security has become more prevalent as more organisations are relying on cyber-enabled infrastructures to conduct their daily actives. Subsequently cybercrime and cyber-attacks are increasing. An Intrusion Detection System (IDS) is a cyber-security tool that is used to mitigate cyber-attacks. An IDS is a system deployed to monitor network traffic and trigger an alert when unauthorised activity has been detected. It is important for IDSs to accurately identify cyber-attacks against assets on cyber-enabled infrastructures, while also being efficient at processing current and predicted network traffic flows. The purpose of the paper is to outline the importance of developing an accurate and effective intrusion detection approach that can be deployed on an IDS. Further research aims to develop a hybrid data mining intrusion detection approach that uses Decision Tree classifications and Association Rules to extract rules using the classified data.
DOI
10.4225/75/57b3f841fb88b
Comments
13th Australian Digital Forensics Conference, held from the 30 November – 2 December, 2015 (pp. 70-76), Edith Cowan University Joondalup Campus, Perth, Western Australia.