Intruder Attack Detection In Data Network Organization Using Data Mining Techniques
DOI:
https://doi.org/10.26438/ijcse/v6i4.544549Keywords:
Data network, attacks, data mining, IDS/IPS machine learningAbstract
Networked data contain interconnected entities for which inferences are to be made. For example, web pages are interconnected by hyperlinks, research papers are associated by references, phone accounts are linked by calls, conceivable terrorists are linked by communications. Networks have turned out to be ubiquitous. Correspondence networks, financial transaction networks, networks portraying physical systems, and social networks are all ending up noticeably progressively important in our everyday life. Regularly, we are interested in models of how nodes in the system influence each other (for example, who taints whom in an epidemiological system), models for predicting an attribute of intrigue in light of observed attributes of objects in the system. The technique of SVM is applied which will classify the data into malicious and non-malicious. To increase the accuracy of classification technique Knn classier is applied which increase accuracy, execution time.
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