A Review of Intrusion Detection and Blockchain Applications in the Cloud: Approaches, Challenges and Solutions

被引:48
作者
Alkadi, Osama [1 ]
Moustafa, Nour [1 ]
Turnbull, Benjamin [1 ]
机构
[1] Univ New South Wales, Sch Engn & Informat Technol, ADFA, Canberra, ACT 2612, Australia
关键词
Intrusion detection systems; collaborative anomaly detection; cloud systems; blockchain applications; approaches; challenges; solutions; DEEP LEARNING APPROACH; ANOMALY DETECTION; DETECTION SYSTEM; SECURITY ISSUES; NETWORK; INTERNET; BITCOIN; DOCKER; LOCALIZATION; TECHNOLOGIES;
D O I
10.1109/ACCESS.2020.2999715
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper reviews the background and related studies in the areas of cloud systems, intrusion detection and blockchain applications against cyber attacks. This work aims to discuss collaborative anomaly detection systems for discovering insider and outsider attacks from cloud centres, including the technologies of virtualisation and containerisation, along with trusting intrusion detection and cloud systems using blockchain. Moreover, the ability to detect such malicious attacks is critical for conducting necessary mitigation, at an early stage, to minimise the impact of disruption and restore cloud operations and their live migration processes. This paper presents an overview of cloud architecture and categorises potential state-of-the-art security events based on their occurrence at different cloud deployment models. Network Intrusion Detection Systems (NIDS) in the cloud, involving types of classification and common detection approaches, are also described. Collaborative NIDSs for cloud-based blockchain applications are also explained to demonstrate how blockchain can address challenges related to data privacy and trust management. A summary of the research challenges and future research directions in these fields is also explained.
引用
收藏
页码:104893 / 104917
页数:25
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