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).