Cloud computing has become a powerful and indispensable technology for, high performance and scalable computation. The exponential expansion the deployment of cloud technology has produced a massive amount of data a variety of applications, resources and platforms. In turn, the rapid and volume of data creation has begun to pose significant challenges for management and security. The design and deployment of intrusion detection (IDS) in the big data setting has, therefore, become a topic of. In this paper, we conduct a systematic literature review (SLR) of mining techniques (DMT) used in IDS-based solutions through the period2013-2018. We employed criterion-based, purposive sampling identifying 32, which constitute the primary source of the present survey. After a investigation of these articles, we identified 17 separate DMTs in an IDS context. This paper also presents the merits and of the various works of current research that implemented DMTs distributed streaming frameworks (DSF) to detect and/or prevent malicious in a big data environment.
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Salo et al. (2020) studied this question.