Machine learning models for enhancing cyber security
by P.R. Therasa; M. Shanmuganathan; B.R. Tapas Bapu; N. Sankarram
International Journal of Electronic Security and Digital Forensics (IJESDF), Vol. 16, No. 5, 2024

Abstract: Because networks are having an ever-increasing impact on contemporary life, cybersecurity has become an increasingly essential area of research. Virus protection, firewalls, intrusion detection systems, and other related technologies are the primary focus of most cybersecurity strategies. These methods defend networks against assaults from both within and outside the organisation. The ever-increasing complexity of deep learning as well as machine learning-based technologies has been applied in the detection and prevention of possible threats. The objective of this research is to investigate and expand upon the applications of machine learning techniques within the context of the topic of cybersecurity. We offer accessible a multi-layered system that is built on machine learning with the intention of modelling cybersecurity. This will be our key area of focus as we work toward achieving our goal of guiding the application toward data-driven, intelligent decision-making for the aim of protecting systems from being attacked by cybercriminals.

Online publication date: Mon, 02-Sep-2024

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