Immunocomputing Model of Intrusion Detection

Melnikov, Yuri B.; Tarakanov, Alexander O.

doi:10.1007/978-3-540-45215-7_44

Cited by 5 publications

(2 citation statements)

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“…1. methods inspired by the immune system that employ conventional algorithms, for example, IBM's virus detector [76] 2. the negative selection paradigm as introduced by Forrest [106] [45] 3. approaches that exploit the Danger Theory [93] In addition, there are several younger methods such as AINET [27] and immunocomputing [94] that continue to grow in popularity. The following subsections explore all the philosophies behind AIS for intrusion detection and analyse their successes and capabilities to date.…”

Section: Immune System Approaches To Idsmentioning

confidence: 99%

“…They claimed that it would be more efficient and easier to detect non-self by building self patterns when a given self space is relatively small, and believed that the identification of self keystroke behaviours belonged to such a case. Melnikov and Tarakanov briefly introduced an immunocomputing model for IDS in [94]. Their model works on a simple test problem, but further results are being produced at the time of writing and may prove promising.…”

Section: Other Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Immune system approaches to intrusion detection – a review

et al. 2007

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Abstract. The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we collate the algorithms used, the development of the systems and the outcome of their implementation. It provides an introduction and review of the key developments within this field, in addition to making suggestions for future research.

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Section: Immune System Approaches To Idsmentioning

confidence: 99%

Section: Other Algorithmsmentioning

confidence: 99%