Feature Selection for Intrusion Detection Systems (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
100
Utgivningsdatum
2014-01-29
Förlag
LAP Lambert Academic Publishing
Medarbetare
Kumar Krishan / Kumar Gulshan
Illustrationer
black & white illustrations
Antal komponenter
1
Komponenter
Paperback
ISBN
9783659515101
Feature Selection for Intrusion Detection Systems (häftad)

Feature Selection for Intrusion Detection Systems

Using data mining techniques

Häftad Engelska, 2014-01-29
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Network security is a serious global concern. The increasing prevalence of malware and incidents of attacks hinders the utilization of the Internet to its greatest benefit and incur significant economic losses. The traditional approaches in securing systems against threats are designing mechanisms that create a protective shield, almost always with vulnerabilities. This has created Intrusion Detection Systems to be developed that complement traditional approaches. However, with the advancement of computer technology, the behavior of intrusions has become complex that makes the work of security experts hard to analyze and detect intrusions. In order to address these challenges, data mining techniques have become a possible solution. However, the performance of data mining algorithms is affected when no optimized features are provided. This is because, complex relationships can be seen as well between the features and intrusion classes contributing to high computational costs in processing tasks, subsequently leads to delays in identifying intrusions. Feature selection is thus important in detecting intrusions by allowing the data mining system to focus on what is really important.
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