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All Journal International Journal of Electrical and Computer Engineering
Serri Faisal
Liwa College of Technology
Computer Science & IT Electrical & Electronics Engineering

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Machine and deep learning techniques for detecting internet protocol version six attacks: a review Arkan Hammoodi Hasan Kabla; Mohammed Anbar; Shady Hamouda; Abdullah Ahmed Bahashwan; Taief Alaa Al-Amiedy; Iznan Husainy Hasbullah; Serri Faisal
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5617-5631

Abstract

The rapid development of information and communication technologies has increased the demand for internet-facing devices that require publicly accessible internet protocol (IP) addresses, resulting in the depletion of internet protocol version 4 (IPv4) address space. As a result, internet protocol version 6 (IPv6) was designed to address this issue. However, IPv6 is still not widely used because of security concerns. An intrusion detection system (IDS) is one example of a security mechanism used to secure networks. Lately, the use of machine learning (ML) or deep learning (DL) detection models in IDSs is gaining popularity due to their ability to detect threats on IPv6 networks accurately. However, there is an apparent lack of studies that review ML and DL in IDS. Even the existing reviews of ML and DL fail to compare those techniques. Thus, this paper comprehensively elucidates ML and DL techniques and IPv6-based distributed denial of service (DDoS) attacks. Additionally, this paper includes a qualitative comparison with other related works. Moreover, this work also thoroughly reviews the existing ML and DL-based IDSs for detecting IPv6 and IPv4 attacks. Lastly, researchers could use this review as a guide in the future to improve their work on DL and ML-based IDS.
Co-Authors Abdullah Ahmed Bahashwan Arkan Hammoodi Hasan Kabla Iznan Husainy Hasbullah Mohammed Anbar Shady Hamouda Taief Alaa Al-Amiedy