@inproceedings{bdec31bff0ae485fb0a68544070d4fff,
title = "Malicious behavior pattern mining using Control Flow Graph",
abstract = "Cyber hacking attacks based on malicious code are becoming diversified. Malicious code analysis is very important because static flow analysis can naturally be helpful as part of the detection process given that malicious codes can affect the data and control flow of a program. This paper introduces the representation method of the Control Flow Graph based on malicious codes. Our proposed method can detect well-known malicious codes and their variants. In addition, the proposed method shows a new response method through the conceptual approach method of source codes.",
keywords = "Control Flow Graph, Graph mining, Malicious behavior",
author = "Chang Choi and Xuefeng Piao and Junho Choi and Mungyu Lee and Pankoo Kim",
note = "Publisher Copyright: {\textcopyright} 2015 ACM.; Research in Adaptive and Convergent Systems, RACS 2015 ; Conference date: 09-10-2015 Through 12-10-2015",
year = "2015",
month = oct,
day = "9",
doi = "10.1145/2811411.2811518",
language = "英语",
series = "Proceeding of the 2015 Research in Adaptive and Convergent Systems, RACS 2015",
publisher = "Association for Computing Machinery, Inc",
pages = "119--122",
booktitle = "Proceeding of the 2015 Research in Adaptive and Convergent Systems, RACS 2015",
}