Artificial intelligence in cyber security: research advances, challenges, and opportunities

Z Zhang, H Ning, F Shi, F Farha, Y Xu, J Xu… - Artificial Intelligence …, 2022 - Springer
In recent times, there have been attempts to leverage artificial intelligence (AI) techniques in
a broad range of cyber security applications. Therefore, this paper surveys the existing …

A systematic review on hybrid intrusion detection system

EM Maseno, Z Wang, H Xing - Security and Communication …, 2022 - Wiley Online Library
As computer networks keep growing at a high rate, achieving confidentiality, integrity, and
availability of the information system is essential. Intrusion detection systems (IDSs) have …

Machine-learning-based DDoS attack detection using mutual information and random forest feature importance method

M Alduailij, QW Khan, M Tahir, M Sardaraz, M Alduailij… - Symmetry, 2022 - mdpi.com
Cloud computing facilitates the users with on-demand services over the Internet. The
services are accessible from anywhere at any time. Despite the valuable services, the …

An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment

R SaiSindhuTheja, GK Shyam - Applied Soft Computing, 2021 - Elsevier
Abstract Detection of Denial of Service (DoS) attack is one of the most critical issues in cloud
computing. The attack detection framework is very complex due to the nonlinear thought of …

Machine learning in network anomaly detection: A survey

S Wang, JF Balarezo, S Kandeepan… - IEEE …, 2021 - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …

Intrusion detection methods based on integrated deep learning model

Z Wang, Y Liu, D He, S Chan - computers & security, 2021 - Elsevier
Intrusion detection system can effectively identify abnormal data in complex network
environments, which is an effective method to ensure computer network security. Recently …

A survey on the role of artificial intelligence, machine learning and deep learning for cybersecurity attack detection

A Salih, ST Zeebaree, S Ameen… - … & Innovation amid …, 2021 - ieeexplore.ieee.org
With the growing internet services, cybersecurity becomes one of the major research
problems of the modern digital era. Cybersecurity involves techniques to protect and control …

Chronological salp swarm algorithm based deep belief network for intrusion detection in cloud using fuzzy entropy

L Karuppusamy, J Ravi, M Dabbu… - … Journal of Numerical …, 2022 - Wiley Online Library
Cloud computing is susceptible to the existing information technology attacks, as it extends
and uses the traditional operating system, information technology infrastructure, and …

Deep reinforcement learning based intrusion detection system for cloud infrastructure

K Sethi, R Kumar, N Prajapati… - … Systems & NETworkS …, 2020 - ieeexplore.ieee.org
Intrusion Detection in cloud platform is a challenging problem due to its extensive usage and
distributed nature that are constant targets of new and unknown attacks. Intrusion detection …

Intrusion detection systems in the cloud computing: A comprehensive and deep literature review

Z Liu, B Xu, B Cheng, X Hu… - … : Practice and Experience, 2022 - Wiley Online Library
Abrupt development of resources and rising expenses of infrastructure are leading
institutions to take on cloud computing. Albeit, the cloud environment is vulnerable to various …