A Systematic Survey on recent Deep Learning trends in Intrusion Detection System
Mukul Soni, Mayank Singhal, Jatin Jatin, Rahul Katarya · 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) · 2021
With the recent growth in the use of communication networks along with data processing systems, there has also been an increasing trend of growing complexity in the volume and variety of data flowing over the internet. Proportionally, the volume and complexity of malicious activities for gaining access to important data has also increased manifolds and thus has become a global headache. Recently, deep learning-based solutions have been found to be quite effective in dealing with intrusion detection and related areas. For the purpose of analyzing deep learning as a key solution to intrusion detection, this paper tries to investigate various deep learning-based approaches for detecting intrusions along with describing their main contributions and capabilities. The growing intensity of attacks, along with the capability of the attackers, existing methods may get bypassed and it is relevant that new techniques are developed. Therefore, in parallel to the ongoing research, a comprehensive analysis of various methods also becomes important. By presenting an expository study of numerous modern methods, this paper provides a strong foundation for the future research work in this domain.