A Comprehensive Survey of Intrusion Detection System Using Machine Learning and Deep Learning Approaches
Kotnur Abhiram, Hariharan Muthusamy, Sindhu Ravindran, Vikneswaran Vijean · 2024
The necessity for Computer networks' use is expanding quickly, which raises problems with preserving network secrecy, availability, and integrity. Intrusion can be defined as an intentional breach of security rules within a secured network. Such intrusions can be identified by an Intrusion Detection system which searches for any malicious actions and recognized dangers within a secured network. Intrusion detection systems patrol the traffic passing through computer systems and give out notifications when they do. Recently, an immense upsurge in cyber-attack cases on computer networks has imposed the need for an effective Intrusion detection system than ever before. Nowadays, network administrators are utilizing multivarious kinds of Intrusion Detection Systems (IDS), in order to monitor network traffic for malicious and unauthorized activities. This review paper focuses on various research works that has developed an approach for evaluating or identifying IDS using many kinds of Machine Learning (ML) and Deep Learning (DL) techniques.