Review on Machine Learning based Network Intrusion Detection Techniques

Shashank, K and Balachandra, Mamatha (2018) Review on Machine Learning based Network Intrusion Detection Techniques. In: International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, 13/08/2018, MITE Moodabidri, Mangalore.

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The security given to a network from unapproved access and dangers is broadly called as network security. It is the obligation of network managers to embrace preventive measures to shield their networks from potential security dangers. Computer networks that are associated with consistent data transactions inside the administration or business require security. The exponential development in the information that streams inside network, the quantity of individuals active on network, makes it essential to have a productive system that disallows outsiders to attack and access secret information. Consistently developing digital attacks should be checked to defend classified information. Machine learning methods which have a critical part in distinguishing the attacks are for the most part utilized as a part of the advancement of Intrusion Detection Systems. Because of colossal increment in network activity and diverse sorts of attacks, checking every single parcel in the system movement is tedious and computational serious

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Network security, Machine learning, SVM, Naïve Bayes, Neural network
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 02 Mar 2019 07:05
Last Modified: 02 Mar 2019 07:05

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