A Survey on Network-based Intrusion Detection System using Learning Techniques
Rupal K Panchal, Rupal Snehkunj, Vinaykumar V Panchal · 2024
Nowadays cyber world faces a significant security challenges such as network intrusion attacks, while sharing data through the network. To ensure the security and confidentiality of the data shared through the network, several techniques were developed. The major significant issues obtained in network intrusion are high false alarm rates with low detection rates and speed. Various learning techniques are introduced to evaluate the network intrusion detection. This review study analyzes different attack types, defense mechanisms, and recent scientific investigations conducted in this field in addition to discussing about the intrusion detection systems, and methodology with the exploration of its challenges along with the future scope. Furthermore, the review provides information about the accessible datasets, well-known IDS tools, and detailed explanations of the benefits and drawbacks of specific IDSs. This study evaluates 25 existing research articles with the analysis of diverse techniques and approaches that are examined under various datasets. In addition to this, the evaluation of distinct performance metrics is briefly discussed. The limitations and future scope of each method will be assessed and the major significance of intrusion detection methods present the road map for future researchers focusing on network attack detection.