A Brief Review of Application of Machine Learning Techniques for Intrusion Detection |
Author(s): |
| Akshita Sharma Mishra , Acropolis Institute of Technology & Research ; Dr. Archana Thakur , School of Computer Science &IT, Devi Ahilya University |
Keywords: |
| Intrusion Detection; Machine Learning; Cyber Analytics; Classification, Clustering |
Abstract |
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With the increased importance of Network in our lives and ever increasing network traffic and vulnerability of networks and increasing security threats in network, it has become critically important to detect threats in real time and save our systems and data from any type of damage. Based on literature, this review provides the details of recent advancements in the field of Intrusion detection, using Machine Learning approaches. We have used CICIDS 2017 dataset, which consist of benign and recent attacks, which are widespread now a day. The supervise methods used are decision tress classifier, naïve bayes classifier, k-nearest neighbor and support vector machines. |
Other Details |
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Paper ID: IJSRDV8I40581 Published in: Volume : 8, Issue : 4 Publication Date: 01/07/2020 Page(s): 308-311 |
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