Control Flow Graphs Against Malware: Methods of Analysis and Detection

One key component of a cyberattack is malware. If a mal ware program is detected and blocked the cyberattack may stagger or fail, thus bad actors design their mal ware programs with additional characteristics and functionalities that harden the analysis of the mal ware program and make the malware undetectable by antivirus solutions. With the appearance of more advanced malware new detection methods are needed. With the help of reverse engineering techniques and software engineering concepts, one model that analysts can work with is Control Flow Graphs. Used for software optimization, control-flow-graphs offer the advantage of graph properties for analysts to detect malicious particularities in malware samples. This paper explores some methods of detection and analysis based on control flow graphs, categorizes them in four categories and highlights different particularities in these approaches.