Uncovering Malware Traits Using Hybrid Analysis

Uncovering Malware Traits Using Hybrid Analysis

연구 분야: Safety

학회: ICONETSI '20: Proceedings of the 2020 International Conference on Engineering and Information Technology for Sustainable Industry

Malware, its volume increases each year and its threat becoming ever more prevalent, is responsible for a large portion of security incidents. Unfortunately, most of the time information regarding the threat that it poses are notional. In this paper, we conduct heuristic static and dynamic analysis in order to extract the necessary static analysis and dynamic analysis features for detecting, assessing and measuring malware threats. Based on the given datasets, i.e. 876 malware and 49 benignware, our proposed method was able to quantitatively assess the threat level of malware and detect malware with promising results.