TY - GEN
T1 - Review on Network Intrusion Detection Techniques using Machine Learning
AU - Shashank, K.
AU - Balachandra, Mamatha
PY - 2019/3/25
Y1 - 2019/3/25
N2 - 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 computationally expensive.
AB - 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 computationally expensive.
UR - http://www.scopus.com/inward/record.url?scp=85064224563&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064224563&partnerID=8YFLogxK
U2 - 10.1109/DISCOVER.2018.8673974
DO - 10.1109/DISCOVER.2018.8673974
M3 - Conference contribution
AN - SCOPUS:85064224563
T3 - 2018 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2018 - Proceedings
SP - 104
EP - 109
BT - 2018 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2018
Y2 - 13 August 2018 through 14 August 2018
ER -