TY - GEN
T1 - Unveiling the Landscape of Machine Learning and Deep Learning Methodologies in Network Security
T2 - 2nd International Conference on Cyber Resilience, ICCR 2024
AU - Saeed, Nouf Majid Sultan Eid
AU - Ibrahim, Amer
AU - Ali, Liaqat
AU - Al-Dmour, Nidal A.
AU - Mohammed, Abdul Salam
AU - Ghazal, Taher M.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The dynamic nature of cyber threats offers a continual problem in the field of cybersecurity in the context of the expanding internet environment. This study provides an in-depth assessment of the literature on machine learning (ML) and deep learning (DL) methodologies for network analysis for intrusion detection. This review curates, assesses, and distils method-specific findings while considering temporal or thermal correlations. It provides a recognition of the importance of data in ML and DL approaches, and a comprehensive overview of frequently used network datasets in ML/DL applications, as well as the inherent challenges of adopting ML/DL in the cybersecurity field. The study concludes with well-informed recommendations for future areas of research in this critical domine.
AB - The dynamic nature of cyber threats offers a continual problem in the field of cybersecurity in the context of the expanding internet environment. This study provides an in-depth assessment of the literature on machine learning (ML) and deep learning (DL) methodologies for network analysis for intrusion detection. This review curates, assesses, and distils method-specific findings while considering temporal or thermal correlations. It provides a recognition of the importance of data in ML and DL approaches, and a comprehensive overview of frequently used network datasets in ML/DL applications, as well as the inherent challenges of adopting ML/DL in the cybersecurity field. The study concludes with well-informed recommendations for future areas of research in this critical domine.
UR - http://www.scopus.com/inward/record.url?scp=85195147836&partnerID=8YFLogxK
U2 - 10.1109/ICCR61006.2024.10533066
DO - 10.1109/ICCR61006.2024.10533066
M3 - Conference contribution
AN - SCOPUS:85195147836
T3 - 2nd International Conference on Cyber Resilience, ICCR 2024
BT - 2nd International Conference on Cyber Resilience, ICCR 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 February 2024 through 28 February 2024
ER -