Abstract--Conversely, limiting access to the information in the interests of preserving secrecy might damage their ability to implement the actions that can best serve the organization. Therefore, data leakage and data misuse detection mechanisms are essential in identifying malicious insiders. One of the emerging concept in micro data protection is kanonymity, which has been recently proposed ...

ion-Based Intrusion Detection The implementation of many misuse detection approaches shares a common problem: Each system is written for a single environment and has proved difficult to use in other environments that may have similar policies and concerns. The primary goal of abstraction-based intrusion detection is to address this problem.

It is widely accepted that there is a strong correlation between diversity in the initial population and Genetic Algorithms’ performance. One contribution of this paper is to show that there is not such a strong correlation between diversity and Genetic Algorithms’ performance, at least with the standard range of diversity measures used in a randomly generated population and with the misuse det...

It is important to increase the detection rate for known intrusions and detect unknown intrusions. It is also important to incrementally learn new unknown intrusions. Most current intrusion detection systems employ either misuse detection or anomaly detection. In order to employ these techniques, we propose incremental hybrid intrusion detection system. This framework combines incremental misus...

Network security is a branch of network management in which network intrusion detection systems provide attack detection features by monitorization of traffic data. Rule-based misuse detection systems use a set of rules or signatures to detect attacks that exploit a particular vulnerability. These rules have to be handcoded by experts to properly identify vulnerabilities, which results in misus...

In this paper, a boosting-based incremental hybrid intrusion detection system is introduced. This system combines incremental misuse detection and incremental anomaly detection. We use boosting ensemble of weak classifiers to implement misuse intrusion detection system. It can identify new classes types of intrusions that do not exist in the training dataset for incremental misuse detection. As...

In the area of intrusion detection the misuse detection approach assumes that relevant activity violating security policies is known a priori and it provides for fast intrusion detection with low false alarm rate, thereby complementing the anomaly detection approach. Hence, misuse detection is an indispensable ingredient to a suitable strategy for intrusion detection. Misuse detection calls for...

Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers an intrusion detection system is a layered framework mechanism designed to support homogeneous network envi...

Intrusion detection is so much popular since the last two decades where intrusion is attempted to break into or misuse the system. It is mainly of two types based on the intrusions, first is Misuse or signature based detection and the other is Anomaly detection. In this paper Machine learning based methods which are one of the types of Anomaly detection techniques is discussed.

The Internet is being used by increasing number of users day by day. Security is a big issue for all networks in today’s enterprise environment. The security of a computer is compromised when an intrusion takes place. Many methods have been developed to secure the network infrastructure and communication over the Internet, among them the use of encryption algorithm, virtual private network and ...