Efficient Machine Learning Techniques for Intrusion Detection System in WSN

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dc.categoryJournal Article
dc.contributor.authorKalpana, B
dc.date.accessioned2017-03-29T23:18:14Z
dc.date.available2017-03-29T23:18:14Z
dc.date.issued2015
dc.departmentComputer Scienceen_US
dc.description.abstractDue to the tremendous growth of Wireless Sensor Network (WSN) in various area especially military application, environment monitoring, health care application, home automation, etc., they are highly exposed to the security threats as well as online fraud. Intrusion Detection System (IDS) are the major research problem and an effective method to detect and analyze various kinds of attack in an internetwork system. Intrusion Detection System (IDS) is mainly designed for security purpose by alerting administrator automatically when someone or something is trying to compromise information system through malicious activities or through security policy violations. Therefore, developing IDS for WSN have attracted many recently and thus, there are many enhanced machine learning techniques that are integrated with IDS to identify unusual access or attacks that approach network system.en_US
dc.identifier.urihttps://ir.avinuty.ac.in/handle/avu/2326
dc.langEnglishen_US
dc.publisher.nameInternational Journal of Emerging Trends In Engineering And Developmenten_US
dc.publisher.typeInternationalen_US
dc.titleEfficient Machine Learning Techniques for Intrusion Detection System in WSNen_US
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