Revathy, G. and Rajendran, V. and Sathish Kumar, P. and Vinuharini, S. and Roopa, G. N. (2022) Smurf attack using hybrid machine learning technique. In: INTERNATIONAL CONFERENCE ON RECENT INNOVATIONS IN SCIENCE AND TECHNOLOGY (RIST 2021), 19–20 June 2021, Malappuram, India.
Full text not available from this repository. (Request a copy)Abstract
Several techniques have been constructed to make the network environment and also better communication very safe and secure in cyber security domain. Intrusion detection system tool plays very important role in finding malevolent aligned with cyber security systems. Also, finding one of the kinds of Denial of Service attack which is Smurf attack is a major protection challenges facing in network equipment. Smurf attack is a kind of Denial of Service attack or malicious which should be find out for keeping the information (data) very safe and secure in Cyber security. So, in this paper we introduced machine learning hybrid algorithm in which Nearest Centroid Algorithm attains least prediction time as 0.01% and accuracy measure as 99.6% in detection of the network attacks mainly detecting Smurf attack for preventing the information very secure.
Item Type: | Conference or Workshop Item (Paper) |
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Subjects: | Computer Science Engineering > Machine Learning |
Divisions: | Electronics and Communication Engineering |
Depositing User: | Mr IR Admin |
Date Deposited: | 13 Sep 2024 10:35 |
Last Modified: | 13 Sep 2024 10:35 |
URI: | https://ir.vistas.ac.in/id/eprint/5924 |