Application of Both Static and Dynamic Analysis Methodologies for Malware Detection

Abstract

Currently, the two most rapidly developing fields in IT are Cybersecurity and Artificial Intelligence. Both of these areas intersect significantly—advancements in AI contribute to the growth of the security sector. This is crucial because cybercriminals are also advancing, devising new methods to cause harm, such as data theft, hijacking infrastructure, turning off IT systems, or espionage.
To prevent such incidents, security specialists are developing increasingly sophisticated tools that enable the detection and neutralization of attacks. Among these tools are two techniques: static analysis and dynamic analysis. In this thesis, both methods have been thoroughly examined, and the benefits of combining these techniques in the context of protection against malware have been demonstrated using specific malicious software.