The architecture of a network level intrusion detection system

Heady, R.; Luger, George F.; Maccabe, A.B.; Servilla, Mark

doi:10.2172/425295

Cited by 225 publications

(129 citation statements)

References 3 publications

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“…We add to this de®nition the identi®cation of attempts to use a computer system without authorization or to abuse existing privileges. Our working de®nition matches the one given by Heady et al [15], where an intrusion is de®ned as``any set of actions that attempt to compromise the integrity, con®dentiality, or availability of a resource'', disregarding the success or failure of those actions.…”

Section: Intrusion Detectionmentioning

confidence: 86%

Intrusion detection using autonomous agents

2000

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AAFID is a distributed intrusion detection architecture and system, developed in CERIAS at Purdue University. AAFID was the ®rst architecture that proposed the use of autonomous agents for doing intrusion detection. With its prototype implementation, it constitutes a useful framework for the research and testing of intrusion detection algorithms and mechanisms. We describe the AAFID architecture and the existing prototype, as well as some design and implementation experiences and future research issues. Ó

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Section: Intrusion Detectionmentioning

confidence: 86%

Intrusion detection using autonomous agents

2000

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“…Intrusion Detection is defined as "the problem of identifying individuals who are using a computer system without authorization (i.e., crackers) and those who have legitimate access to the system but are abusing their privileges (i.e., insider attack: threat)" [1]. An Intrusion Detection System gathers and analyzes information from various areas within a computer or a network to identify possible security breaches, which include both intrusions (attacks from outside the organization) and misuse (attacks from within the organization).…”

Section: C) Availabilitymentioning

confidence: 99%

An Approach for Collaborative Decision in Distributed Intrusion Detection System

Sharma¹,

Singh²

2016

IJCA

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Computers have virtually changed every aspect of our life. The rapid growth in the development of computers was focused on making the computer easy to use for all. The rapid growth did not give as much importance on the security of the computer system thereby leaving system as vulnerable to attacks. As internet and its applications are increasing, complex and hybrid networks are being used for communication. So many loopholes are being explored to intrude into other systems. There are many tools and techniques available for securing networks like Firewalls, IDS etc. and until now they are used very frequently by nearly all the organizations to safeguard information and other critical data but these are not sufficient for implementing complete security because the intruders have become smarter.Higher security being the priority of many organizations has led to the importance and promoting active research on efficient Intrusion Detection Systems. To deal with various types of attacks we need to have information of attacks from other sources as well. This can be done by sharing intrusion information with all. As hackers are becoming more intelligent we need to have collaborative decision making system where intrusion activity is decided by knowing other's opinion as well. We have proposed an approach to enhance the collaborative decision making by conducting polls between registered intrusion detection systems in the network. Intrusion activity for new packets and false positives is decided based on all opinions gathered from registered intrusion detection systems.

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“…The intrusion can be caused by inside (legal users), or outside (illegal users) in the system [2]. Nowadays recognition and prevention of intrusion is one of the most important mechanisms that provides security in networks and computer systems, and generally is used as a complemented security for firewalls [3].…”

Section: Intrusion Detection Systemmentioning

confidence: 99%

Role of Support Vector Machine Fuzzy KMeans and Naive Bayes Classification in Intrusion Detection System

Mudgal¹

2015

IJRITCC

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Abstract:-An Intrusion can be defined as the access to unauthorised user, a breach in a security, misuse of the information or the system which can be done both internally and externally of the organization. So, Intrusion Detection is basically providing the security or managing the flow of data, information, managing the access of the system to only authorised user. In a network which is widely distributed requires high end security, only authorised user can access the system in a network. So, it requires more than authentication, providing passwords or certificates. An Intrusion Detection system is used to detect and monitor the number of happenings and episode in a network or a system. It will gather the information and analyse that information. If, it finds any unauthorized access or misuse it will detect it as Intrusion and will follow provided instructions. So, If Intrusion is the violation of security, then Detection is the management and taking necessary action against that Intrusion. For detecting any Intrusion in a network or system there are number of techniques which are used and can be developed to prevent.

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The architecture of a network level intrusion detection system

Cited by 225 publications

References 3 publications

Intrusion detection using autonomous agents

Intrusion detection using autonomous agents

An Approach for Collaborative Decision in Distributed Intrusion Detection System

Role of Support Vector Machine Fuzzy KMeans and Naive Bayes Classification in Intrusion Detection System

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