Enhancing Android Security: Static Analysis for Robust Protection and Resilient Defences using Deep Learning

Android has been a popular target for criminal actions due to its widespread use as a prominent mobile operating system, requiring the creation of sufficient security measures. Android has grown exposed to illegal activities due to its open-source design and ability to install third-party apps without centralized oversight. The suggested study thoroughly examines the rights that programs ask for to see whether there are any noticeable differences between the permissions used by malware samples and their benign equivalents. Based on complex authorization patterns, various machine learning methods are applied to distinguish between the two groups effectively. The discoveries spur the creation of solid security frameworks, eventually reducing the dangers of potential malware attacks.