Artificial Immune Systems (AIS) have long been used in the field of computer security and especially in Intrusion Detection systems. Intrusion detection based on AISs falls into two main categories. The first generation of AIS is inspired from adaptive immune reactions but, the second one which is called danger theory focuses on both adaptive and innate reactions to build a more biologically-re...

Intrusion Detection is one of major threats for organization. The approach of intrusion detection using text processing has been one of research interests which is gaining significant importance from researchers. In text mining based approach for intrusion detection, system calls serve as source for mining and predicting possibility of intrusion or attack. When an application runs, there might ...

Internet provides huge information and value to the users but at the same time access to the internet is prone to increasing number of attacks. Tracing the source of the attacking packet is very difficult because of stateless and destination based routing infrastructure of Internet. If the attacks are detected successfully, then preventive measures for attacks can be taken. Host based and netwo...

In this paper, we in introduce a specification based intrusion detection model for detecting attacks on routing protocols in MANETs. Intrusion detection is a viable approach to enhancing the security of existing computers and networks. Briefly, an intrusion detection system monitors activity in a system or network in order to identify ongoing attacks. Intrusion detection techniques can be class...

Signature based intrusion detection systems cannot detect new attacks. These systems are the most used and developed ones. Current anomaly based intrusion detection systems are also unable to detect all kinds of new attacks because they are designed to restricted applications on limited environment. Current hackers are using new attacks where neither preventive techniques mainly based on access...

With the increased usage of computer networks, security becomes a critical issue. Recently, data mining methods have gained lot of attention in addressing network security issues, including intrusion detection. Consequently, unsupervised learning methods have been given much importance for anomaly based network intrusion detection. In this paper, we investigate new clustering algorithms like fa...

Intrusion Detection Systems (IDS) are a very popular network security tool. These tools can allow network administrators, to identify and react to hostile traffic aimed at, or generated from their own network. In general there are two common Intrusion Detection approaches which are behavior or traffic anomaly based and knowledge or signature based. As a result of the increased sophistication of...

Intrusion detection involves a lot of tools that are used to identify different types of attacks against computer systems and networks. With the development of network technologies and applications network attacks are greatly increasing both in number and severe. Open source and commercial network intrusion detection tools are not able to predict new type of attacks based on the previous attack...

Network Intrusion Detection Systems are nowadays an integral part of network security. NIDS provide a layer of defense by monitoring and analyzing the traffic for signs of suspicious activities and alerting system administrators when potential violations are detected. In the context of large, high-speed networks, such as backbone networks, we make two observations: Firstly, devices capable of d...