딥 러닝 기반 분류 모델을 이용한 악성코드 제작자 그룹 분류

초록

As computers are heavily used in real life, attempts at creating malwares to attack others' computers for malicious purposes are increasing exponentially. Malwares can be categorized based on the group of authors who created the code, and their information is considered to be important for digital forensics. In this paper, we extract the static features and the dynamic features from the malware and use the features to represent the malware by considering the presence or absence of each feature in the malware. Based on the feature information, we proposed a method to classify a group of authors of a given malware by using a deep learning technique. Also, we find a hyperparameter and a deep learning technique that work best on the malware author group classification via extensive experiments. Using these, we construct and evaluate a deep learning based malware author group classification model. We confirmed that the classification accuracy of the proposed model is higher than those of the existing malware author group classification models.

키워드