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文件名称:神经网络在异常入侵检测系统中的应用综述
文件大小:114KB
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更新时间:2022-04-23 16:41:07
神经网络 入侵检测 lunwen
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- Intrusion Detection Systems; Neural Network;
Anomaly Detection
I. INTRODUCTION
Companies and government agencies dependence on
computer networks has never been more critical, and
probability of attacks with devastating consequences has never
been higher, hence the need for protection is becoming no less
critical. Good network security suite should not only be able to
detect attacks or recover from attack but should also have fast
reactionary capabilities. Hacker, attacking from inside as an
authorized user or from outside as an intruder, uses
vulnerabilities or flaws on a system. It is therefore important to
have a tool that monitors activity of users with intent of
detecting malicious activities. This important part of network
security is called Intrusion Detection System (IDS).