Methods of intrusion detection in information security incident detection: a comparative study

Tan, Fui Bee and Yau, Ti Dun and M. N. M., Kahar (2018) Methods of intrusion detection in information security incident detection: a comparative study. In: Proceedings Book: National Conference for Postgraduate Research (NCON-PGR 2018), 28-29 August 2018 , Universiti Malaysia Pahang, Gambang, Pahang. pp. 60-72.. ISBN 978-967-22260-5-5

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The advance development in technology have made internet and online application and network usage become one of the important element in human life. With the high demand from the corporate and enterprise, more and more security appliances were developed and deployed, such as IDS (Intrusion Detection Systems), IPS (Intrusion Prevention Systems), Firewall, and SIEM (Security Information and Event Management). All these security tools have serve same purpose which is to safe guard the whole enterprise network. However, every single tool has different ways of detection and accuracy of the detection. This was due to each solution deploy was highly depended with the algorithms reside in the program loaded in the security tools. These algorithms and methods provide fast and high rate of detection. However, it also produces high false alarm rate (low accuracy) and unable to handle high volume of data. This have attracted researchers to find algorithms and methods that can detect intrusions in a short period of time within a huge volume of data with high accuracy. The objective of this paper is to study and make a comparison among the available intrusion detections algorithms and methods in the intrusion detections. Focus will be given to research that have produced new intrusion detection algorithms, framework and model as well as their gaps in the research. Their research results and gaps can lead to any possible future research to identify new intrusion detection methods.

Item Type: Conference or Workshop Item (Speech)
Uncontrolled Keywords: IDS; IPS; SIEM; Intrusion Detection
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 10 Dec 2018 06:24
Last Modified: 24 Jul 2019 02:14
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