Nowadays Intrusion Detection System (IDS) which is increasingly a key element of system security is used to identify the malicious activities in a computer system or network. There are different approaches being employed in intrusion detection systems, but unluckily each of the technique so far is not entirely ideal. The prediction process may produce false alarms in many anomaly based intrusio...

With the ever increasing use of computers for critical systems, computer security, the protection of data and computer systems from intentional, malicious intervention, is attracting much attention. Among the methods for defence, intrusion detection, i.e. the application of a tool to help the operator identify ongoing or already perpetrated attacks has been the subject of considerable research ...

Computer network systems are constantly under attack or have to deal with attack attempts. The first step in any network’s ability to fight against intrusive attacks is to be able to detect intrusions when they are occurring. Intrusion Detection Systems (IDS) are therefore vital in any kind of network, just as antivirus is a vital part of a computer system. With the increasing computer network ...

In this paper, we focus on one critical issue in security management that is intrusion detection. Intrusion detection requirements and concepts are reviewed. Some existing systems are described. Their advantages and limitations are illustrated. Drawbacks of existing intrusion detection systems involve the necessity of designing a new generation of self-adaptive systems. In fact, mainly, self-co...

In today’s world, almost everybody is affluent with computers and network based technology is growing by leaps and bounds. So, network security has become very important, rather an inevitable part of computer system. An Intrusion Detection System (IDS) is designed to detect system attacks and classify system activities into normal and abnormal form. Machine learning techniques have been applied...

This report explores integrating fuzzy logic with two data mining methods (association rules and frequency episodes) for intrusion detection. Data mining methods are capable of extracting patterns automatically from a large amount of data. The integration with fuzzy logic can produce more abstract and flexible patterns for intrusion detection, since many quantitative features are involved in in...

The advent of computer networks and the Internet has drastically altered means by which we share information & interact with each other. However, this technological advancement also created room for malevolent behaviour where individuals exploit weak points intent gaining access to confidential data, blocking activity etc. To end, intrusion detection systems (IDS) are needed filter malicious tr...