BEHAVIORAL HEURISTIC ADVERSARY RECOGNITION ENGINE (BHARE)

Abstract

Malware detection is a persistent challenge in the ever-evolving landscape of digital threats. As cyber adversaries continuously develop new evasion techniques, traditional signature-based or static analysis approaches prove inadequate against unknown or zero-day malware. This paper introduces BHARE (Behavioral Heuristic Adversary Recognition Engine), a lightweight and efficient behavioral analysis malware detection system. BHARE utilizes advanced behavioral analysis to proactively identify and mitigate threats, particularly on resource-constrained devices such as mobile platforms. The proposed system employs a novel heuristic learning algorithm for continuous improvement in detection capabilities over time, addressing the dynamic nature of malware evolution. BHARE stands as a promising tool for protecting devices from malware infections, particularly in the context of increasing attacks on mobile platforms.