Intrusion detection systems are the foremost tools for providing safety in computer and network system. There are many limitations in traditional IDSs like time consuming statistical analysis, regular updating, non adaptive, accuracy and flexibility. It is an Artificial Neural Network that supports an ideal specification of an Intrusion Detection System and is a solution to the problems of trad...

Intrusion detection is considered to be an effective technique to detect attacks that violate the security policy of systems. There are basically three different kinds of intrusion detection: Anomaly detection, misuse detection and specification-based intrusion detection [MB02]. Specification-based intrusion detection differs from the others by describing the desired functionalities of security...

Intrusion detection system is the indispensable part of every computer. With the increasing attack means, all kinds of intrusion detection methods have appeared. Compared with other intrusion detection methods, the intrusion detection methods based on Conditional Random Fields (CRFs) has better detection effect, but the problems that the accuracy is low when the training data is small and the t...

In the field of network intrusion detection, both the signature-based intrusion detection system and the machine learning-based intrusion detection system possess advantages and disadvantages. When the two discrepant systems are combined in a way that the former is used as the main system and the latter as a supporting system, the machine learning-based intrusion detection system measures the v...

Mobile ad-hoc networks are temporary wireless networks. Network resources are abnormally consumed by intruders. Anomaly and signature based techniques are used for intrusion detection. Classification techniques are used in anomaly based techniques. Intrusion detection techniques are used for the network attack detection process. Two types of intrusion detection systems are available. They are a...

High level security is an essentially required in the communication and information sharing on the network clouds. Intrusion detection system (IDS) is being used to detect violations and malicious behavior over networks and hosts. Purpose of our paper is to provide an Intrusion detection system to detect and prevent the malicious behavior on the cloud computing. We propose an intrusion detectio...

Recently data mining methods have gained importance in addressing network security issues, including network intrusion detection—a challenging task in network security. Intrusion detection systems aim to identify attacks with a high detection rate and a low false alarm rate. Classification-based data mining models for intrusion detection are often ineffective in dealing with dynamic changes in ...

Current intrusion detection systems (IDSs) usually focus on detecting low-level attacks and/or anomalies; none of them can capture the logical steps or attack strategies behind these attacks. Consequently, the IDSs usually generate a large amount of alerts. In situations where there are intensive intrusive actions, not only will actual alerts be mixed with false alerts, but the amount of alerts...

Maintenance or repair of water mains may require the interruption of flow. Re-initiation of flow may present opportunities for the interaction of air and the accelerating water, resulting in undesirable pressure transients. This study focuses on air intrusion during flow startup in an initially filled horizontal pipeline supplied by a constant-head reservoir. Flow was initiated by opening the d...

Designers of intrusion detection systems are often faced with the problem that their design fails to meet the specification because the actual implementation is not able to detect attacks as required. This work aims at addressing such shortcomings at an early stage of the design process. The proposed method provides guidance to intrusion detection systems designers by predicting whether or not ...