As the communication industry has connected distant corners of the globe using advances in network technology, intruders or attackers have also increased attacks on networking infrastructure commensurately. System administrators can attempt to prevent such attacks using intrusion detection tools and systems. There are many commercially available signature-based Intrusion Detection Systems (IDSs...

As the communication industry has connected distant corners of the globe using advances in network technology, intruders or attackers have also increased attacks on networking infrastructure commensurately. System administrators can attempt to prevent such attacks using intrusion detection tools and systems. There are many commercially available signature-based Intrusion Detection Systems (IDSs...

In this paper intrusion detection systems (IDSs) are classified according to the techniques applied to processing input data. This process is complex because IDSs are highly coupled in actual implemented systems. Eleven input data processing techniques associated with intrusion detection systems are identified. They are then grouped into more abstract categories. Some approaches are artificiall...

Cyber intrusion is becoming an increasingly global and urgent problem. Intrusion Detection Systems (IDSs) are deployed to identify intrusions and mitigate their damage. A stand alone IDS does not have complete information or knowledge to detect intrusions. A Collaborative Intrusion Detection Network (CIDN) consists in a set of cooperating IDSs which use collective knowledge and experience to ac...

With the increasing amount of network throughput and security threat, the study of intrusion detection systems (IDSs) has received a lot of attention throughout the computer science field. Current IDSs pose challenges on not only capricious intrusion categories, but also huge computational power. Though there is a number of existing literatures to IDS issues, we attempt to give a more elaborate...

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...

Cloud computing has become an attractive target for attackers as the mainstream technologies in the cloud, such as the virtualization and multitenancy, permit multiple users to utilize the same physical resource, thereby posing the so-called problem of internal facing security. Moreover, the traditional network-based intrusion detection systems (IDSs) are ineffective to be deployed in the cloud...

Intrusion Detection Systems (IDSs) play a significant role in monitoring over Battiti's MIFS method avoiding selection of irrelevant features.

More and more, Intrusion Detection Systems (IDSs) are seen as an important component in comprehensive security solutions. Thus, IDSs are common elements in modern infrastructures to enforce network policies. So far, plenty of techniques have been applied for the detection of intrusions, which has been reported in many surveys. This work focuses the development of network-based IDSs from an arch...

One of most important existent issues in information security application domain is Intrusion Detection System (IDS); IDS is a defensive-aggressive system to protect information, verifying and responding to occurring attacks on computer systems and networks. This paper discusses different topics including presenting some strategies against IDSs to passing from them; this leads to improving dete...