This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid mo...

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...

The goal of this paper is to highlight the useful aspects of Network Intrusion Detection System (NIDS) and Network Intrusion Prevention System (NIPS).

Intrusion-detection systems (IDS) aim at detecting attacks against computer systems and networks or, in general, against information systems. Its basic aim is to protect the system against malwares and unauthorized access of a network or a system. Intrusion Detection is of two types Network-IDS and Host BasedIDS. This paper covers the scope of both the types and their result analysis along with...

Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic Intelligent Intrusion Detection System model, based on specific AI approach for intrusion detection. The technique that...

Nowadays, the protection and the security of data transited within computer networks represent a real challenge for developers of computer applications and network administrators. The Intrusion Detection System and Intrusion Prevention System are the reliable techniques for a Good security. Any detected intrusion is based on data collection. So, the collection of an important and significant tr...

With the growing need of internet in daily life and the dependence on the world wide system of computer networks, the network security is becoming a necessary requirement of our world to secure the confidential information available on the networks. Efficient intrusion detection is needed as a defence of the network system to detect the attacks over the network. Using feature selection, we redu...

This Paper titled “Novel Approach for Intrusion Detection System” is an intrusion detection system (IDS) proposed by analyzing the principle of the intrusion detection system based on host and network. Basically this paper is to develop host based cum network based intrusion detection system for Microsoft Windows XP environment. Proposed concept that had used in this was applying intrusion dete...

efficient intrusion detection is needed as a defense of the network system to detect the attacks over the network. A feature selection and classification based Intrusion Detection model is presented, by implementing feature selection, the dimensions of NSLKDD data set is reduced then by applying machine learning approach, we are able to build Intrusion detection model to find attacks on system ...

In the field of network security, researchers have implemented different models to secure the network. Intrusion Detection System is also one of them and Snort is an open source tool for Intrusion Detection and Prevention System. Today intrusion Detection System is a growing technology in network security and mostly researchers have focused in this field, some of them used signature or rule-bas...