Intelligent Malware Detection Integrating Cloud and Fog Computing

Currently, there is a noticeable increase in the digitization of services provided by companies and government agencies, and there is also an increase in concern about the cybersecurity aspects of corporate and personal data due to the rise of malicious software (Malware). Within this context, this work presents a solution for intelligent Malware detection, applying Artificial Intelligence (AI) techniques on an architecture that integrates cloud computing and fog computing. The solution aims to detect Malware with minimal impact on the user’s device, achieving scalability and adequate response time through data compression and functionality division per environment. The solution is evaluated using real Malware data applied to a real environment, organizing the fog and cloud context. The results demonstrate the solution’s feasibility, where the compression approach achieves about 60% reduction in data communication, while the Malware detection efficiency is around 99% in a few milliseconds.