DocumentCode
2023048
Title
An overview of neural networks use in anomaly Intrusion Detection Systems
Author
Sani, Yusuf ; Mohamedou, Ahmed ; Ali, Khalid ; Farjamfar, Anahita ; Azman, Mohamed ; Shamsuddin, Solahuddin
Author_Institution
Dept. of Commun. Technol. & Networks, Univ. Putra Malaysia, Serdang, Malaysia
fYear
2009
fDate
16-18 Nov. 2009
Firstpage
89
Lastpage
92
Abstract
With the increasing number of computers being connected to the Internet, security of an information system has never been more urgent. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. This is the reason of an entire area of research, called Intrusion Detection Systems (IDS). Anomaly systems detect intrusions by searching for an abnormal system activity. But the main problem of anomaly detection IDS is that; it is very difficult to build, because of the difficulty in defining what is normal and what is abnormal. Neural network with its ability of learning has become one of the most promising techniques to solve this problem. This paper presents an overview of neural networks and their use in building anomaly intrusion systems.
Keywords
learning (artificial intelligence); neural nets; security of data; abnormal system activity search; anomaly systems; intrusion detection systems; learning ability; neural networks; Anomaly Detection; Intrusion Detection Systems; Neural Network;
fLanguage
English
Publisher
ieee
Conference_Titel
Research and Development (SCOReD), 2009 IEEE Student Conference on
Conference_Location
Serdang
Print_ISBN
978-1-4244-5186-9
Electronic_ISBN
978-1-4244-5187-6
Type
conf
DOI
10.1109/SCORED.2009.5443289
Filename
5443289
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