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 ...

as networking and communication technology becomes more widespread, thequantity and impact of system attackers have been increased rapidly. themethodology of intrusion detection (ids) is generally classified into two broadcategories according to the detection approaches: misuse detection and anomalydetection. in misuse detection approach, abnormal system behavior is defined atfirst, and then an...

The goal of this paper is to present designed architecture of intrusion detection system based on events planning and intrusion signature. The article describes problematic of the variation of intrusions and intrusion detection systems. The core of the proposed architecture is intrusion signature matching through petri nets that clasify system behaviour and determine potential intrusion of moni...

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence E...

This paper describes a prototype intelligent intrusion detection system (IIDS) that is being developed to demonstrate the effectiveness of data mining techniques that utilize fuzzy logic. This system combines two distinct intrusion detection approaches: 1) anomaly based intrusion detection using fuzzy data mining techniques, and 2) misuse detection using traditional rule-based expert system tec...

The Fuzzy Intrusion Recognition Engine (FIRE) is an anomaly-based intrusion detection system that uses fuzzy logic to assess whether malicious activity is taking place on a network. It uses simple data mining techniques to process the network input data and help expose metrics that are particularly significant to anomaly detection. These metrics are then evaluated as fuzzy sets. FIRE uses a fuz...

In this paper we propose a distributed agent framework for an intrusion detection system aimed at ad hoc wireless networks. Wireless networks are particularly vulnerable to intrusion, as they operate in an open medium, and use cooperative strategies for network communications. By efficiently merging audit data from multiple security agents, we analyze the entire ad hoc wireless network for intr...

Most of the intrusion detection systems are unable to detect behavior-based intrusions such as Stuxnet, because of their absolute view of the intrusion. There are some legitimate behaviors which their subsequences cause intrusions. In this paper, a multi-agent model inspired by the human immune system has been proposed whose autonomous agents have a conditional view towards intrusion concept. T...