Network Intrusion Detection System using XG Boost
M. S. Siva Priya1, Bipin Kumar Sahu2, Badal Kumar3, Mayank Yadav4
1Bipin Kumar Sahu*,Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
2Bipin Kumar Sahu, Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
3Badal Kumar, Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
4Mayank Yadav, Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
Manuscript received on September 14, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 4070-4073 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1307109119/2019©BEIESP | DOI: 10.35940/ijeat.A1307.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Internet is the most widely used commodity throughout the world. Such widescale adoption of internet has resulted in drastic developments across various facets of life. Several studies indicate a surge in cybercrimes including incidents of personal privacy thefts. Network intrusion is any illegitimate and/or unidentified activity taking place over a network. So, an effective intrusion detection system is required to be developed. Through this paper, we propose an intrusion detection system that uses XG Boost algorithm to detect intrusions. To implement this approach, KDD-99 dataset has been used for inputs. This paper demonstrates that the efficiency and accuracy of intrusion detection system deployed using XG Boost algorithm is better than contemporary algorithms.
Keywords: IDS, Intrusion Detection, KDD-99, XGBoost.