Synthesizing DNAs of a system's binary files from its functional and structural representation

Malware infects system programs or files basically by injecting malicious code into them via a dynamic or static approach. This malicious code will cause the system to malfunction or crash while compromising invaluable vital data. Engineering techniques to curb malicious attacks has been an area of research interest in cybersecurity and malware analysis. After careful examination of the existing work in this domain, we conclude that most of the state-of-the-art research work concentrate on the separate analysis of the behavior of benign and malware programs in order to obtain discriminating feature sets between them. We propose a novel approach to study the behaviors of non-malicious programs (.exe, .dll, etc.) when infected and not infected by malware and then compare those with the behavior of the malware itself. The paper aims to capture these feature sets associated with these three distinct behavioral dynamics, analyze and synthesize them into DNA-like representation (data sets) akin to biological Deoxyribonucleic acid(DNA). These data sets will then be piped into another future phase of this research that aims at developing a malware mitigation model that leverages the CRISPR defense concept, detects zero-day malware and enables recovering (repairing) files infected by malware.