Data mining techniques have been successfully applied in many fields including marketing, manufacturing, process control, fraud detection and network management. In recent years, data mining-based Intrusion Detection Systems (IDS) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. In data mining based intrusion detect...

Due to many inherent deficiencies and flaws, current intrusion detection systems (IDS) are plagued by numerous problems. Intrusion Detection Systems are often inefficient and ineffective when used alone. IDS products need to be fully integrated into the security defense line. Intrusion alert analysis and management are crucial in achieving this. In this paper, we describe an intrusion detection...

Applying intrusion detection to the fast growing computational Grid environments improves the security which is considered to be the heart of this new field. Flexible cooperative distributed intrusion detection architecture is introduced that suits and benefits from the underlying computational Grid environment. The proposed architecture was tested using homogeneous distributed intrusion detect...

Intrusion detection is a major research problem in network security. Due to the nonlinear nature of the intrusion attempts, unpredictable behavior of the network traffic and the large number of features in the problem space, intrusion detection systems represent a complicated problem area. Choosing effective and key features for intrusion detection is a very important topic in information secur...

Data mining for intrusion detection is one of the most cutting-edge researches which focus on network security, database, and information decision-making. Due to the emergence of new forms of attacks and intrusion on the network, we need a new intrusion detection system which would be able to detect new and unknown attacks. In the paper, by studying the characteristics of network data intrusion...

–Nowadays, as information systems are more open to the Internet, the importance of secure networks is tremendously increased. New intelligent Intrusion Detection Systems (IDSs) which are based on sophisticated algorithms rather than current signature-base detections are in demand. There is often the need to update an installed Intrusion Detection System (IDS) due to new attack methods or upgrad...

Intrusion detection for mobile ad hoc network (MANET) is a complex and difficult task due to the nature of the network. The mobile ad hoc network is vulnerable due to its features of open medium, cooperative algorithms, dynamic changing topology, lack of centralized monitoring and management point. The mobile ad hoc networks (MANETs) combine wireless communication with high degree of node mobil...

Intrusion Detection System (IDS) which is increasing the key element of system security is used to identify the malicious activities in a computer system there are different approaches being employed in intrusion detection systems. The prediction process may produce false alarms in many anomaly based intrusion detection systems. With the concept of fuzzy logic, the false alarm rate in establish...

Research in automated computer security intrusion detection, intrusion detection for short, is maturing. Several difficulties remain to be solved before intrusion detection systems become commonplace as part of real-world security solutions. One such difficulty regards the subject of effectiveness, how successful the intrusion detection system is at actually detecting intrusions with a high deg...

KDD 99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers working in the field of intrusion detection and is the only labeled dataset publicly available. Numerous researchers employed the datasets in KDD 99 intrusion detection competition to study the utilization of machine learning for intrusion detection and reported detection rates up to ...