Methodologies for Predicting Cybersecurity Incidents
Yaser M. A. Abualkas1, D. Lalitha Bhaskari2

1Yaser M.A. Abualkas, Research Scholar, Department of Computer Science and Systems Engineering, College of Engineering, Andhra University, Visakhapatnam (A.P), India.

2D. Lalitha Bhaskari, Professor, Department of Computer Science and Systems Engineering, College of Engineering, Andhra University, Visakhapatnam (A.P) India.

Manuscript received on 27 June 2022 | Revised Manuscript received on 21 March 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 1-8 | Volume-3 Issue-1, May 2023 | Retrieval Number: 100.1/ijcns.F36770811622 | DOI: 10.54105/ijcns.F3677.053123

Open Access | Ethics and Policies | Cite | Zenodo | Indexing and Abstracting
© The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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.

Keywords: Cybersecurity, Machine Learning, Data Science, Decision Making, Cyber-Attack, Security Modeling, Intrusion Detection, Cyber Threat Intelligence, Data-Driven, Cybersecurity Incidents.
Scope of the Article: System Security