IDS Using Machine Learning - Current State of Art and Future Directions
Yasir Hamid, M. Sugumaran, V. R. Balasaraswathi
Current Journal of Applied Science and Technology · pp. 1–22 · Published 21 Mar 2016
10.9734/BJAST/2016/23668Abstract
The prosperity of technology worldwide has made the concerns of security tend to increase rapidly. The enormous usage of Internetworking has raised the need of protecting systems as well as networks from the unauthorized access or intrusion. An intrusion is an activity of breaking into the system by compromising the security policies, and the process of analyzing the network data for the possible intrusions is Intrusion Detection. For the last two decades automatic intrusion detection system has been an important research topic. Up to the moment, researchers have developed Intrusion Detection Systems (IDS) capable of detecting attacks in several available environments. A boundlessness of methods for misuse detection as well as anomaly detection has been applied, most popular of the all is using machine learning techniques. In this work a survey of various research efforts spared towards the development of intrusion detection systems based on machine learning techniques in given. The surveyed works are presented in easy to understand tabular forms and for each work; technique employed, dataset used and the parameters evaluated are mentioned. Current achievements and limitations in developing intrusion detection system by machine learning and future directions for research are also given.
Cited by 27
Ying-Dar Lin, Shin-Yi Yang, Didik Sudyana · Computers & Security · 2024
Yasir Hamid, M. Sugumaran, Ludovic Journaux · Proceedings of the International Conference on Informatics and Analytics · 2016
Hafsa Benaddi, Khalil Ibrahimi, Abderrahim Benslimane · Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · 2020
Huma Gupta, Akshay Jadhav, Abhay Singh Bisht · International Journal of Networked and Distributed Computing · 2025
Mouad Choukhairi, Mohamed M’Haouach, Youssef Fakhri · 2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM) · 2023
William Taylor, Syed Aziz Shah, Kia Dashtipour · Sensors · 2020
Jia Jingping, Chen Kehua, Chen Jia · IEEE Access · 2019
Yasir Hamid, Firdous A Shah, M. Sugumaran · International Journal of Information Technology · 2018
Abhilash Chakraborty, Anupam Biswas, Ajoy Kumar Khan · Intelligent Systems Reference Library · 2023
Hafsa BENADDI, Khalil IBRAHIMI, Abderrahim BENSLIMANE · 2018 6th International Conference on Wireless Networks and Mobile Communications (WINCOM) · 2018
Showing 20 of 27 known citations — external sources report more than can currently be individually listed.
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