DEEP LEARNING APPROACHES FOR SECURITY MECHANISMS IN OPERATING SYSTEMS: A REVIEW
Keywords:
Operational Security, Deep Learning, Operating System, Convolutional Neural Networks (CNNs), Long ShortTerm Memory (LSTM), Machine Learning, attack prevention mechanisms, malware detection.Abstract
Operating systems are the workhorses of modern computing, and securing the OS is critical to protecting data from malware in today's cyber threat landscape. The rapid development of novel cyber threats has made it difficult for existing security measures to stay on the ball, consequently attaining a wide hole between detection and prevention of new types of advanced attacks. Operational mechanisms on the system, new threats and solutions, or any other related discussion becomes a crucial part of this mechanism Hence In order to find most suitable techniques along with algorithms for aiding in detecting and preventing Cyber Attacks, This paper has structured systematic literature review which depicts various possible ways that automate certain operations using deep learning way. This review aims to bridge this gap by providing an overview of recent research on OS security, with the goal of enriching the design of more secure and resilient OS security mechanisms against such attacks.
