Methodologies for Predicting Cybersecurity Incidents
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Abstract
Data science may be used to detect, prevent, and address ever-evolving cybersecurity risks. CSDS is a fast developing field. When it comes to cybersecurity, CSDS emphasises the use of data, concentrates on generating warnings that are specific to a particular threat and uses inferential methods to categorise user behaviour in the process of attempting to enhance cybersecurity operations. Data science is at the heart of recent developments in cybersecurity technology and operations. Automation and intelligence in security systems are only possible through the extraction of patterns and insights from cybersecurity data, as well as the creation of data-driven models that reflect those patterns and insights An attempt is made in this work to describe the various data-driven research approaches with a focus on security. In accordance with the phases of the technique, each work that anticipates cyber-incidents is thoroughly investigated to create an automated and intelligent security system.
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