A Malware Behavior Analysis Method based on Coupling Degree

被引:0
|
作者
Guo Gang [1 ]
Wei Sheng-jun [2 ]
机构
[1] Beijing Inst Technol, Beijing Key Lab Software Secur Engn, Sch Comp Sci & Technol, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Beijing Key Lab Software Secur Engn Technol, Beijing 100081, Peoples R China
关键词
obfuscation technique; Data fusion; coupling degree;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aiming at the malware obfuscation technique, a new software behavior analysis method is proposed in the paper. The instruction coupling degree is calculated through mapping and associating the code analysis and log analysis to judge whether the instructions belong to the same behavior and then obtain the instruction information and operation process of different behaviors. The experiment proves that the method can effectively avoid the interference caused by the obfuscation techniques with the characteristics of good fault tolerance and high analysis accuracy.
引用
收藏
页码:582 / 590
页数:9
相关论文
共 50 条
  • [41] A Malware Similarity Analysis Method Based on Network Control Structure Graph
    Wang, Duanyi
    Shu, Hui
    Kang, Fei
    Bu, Wenjuan
    [J]. PROCEEDINGS OF 2020 IEEE 11TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2020), 2020, : 295 - 300
  • [42] A Generic Binary Analysis Method for Malware
    Izumida, Tomonori
    Futatsugi, Kokichi
    Mori, Akira
    [J]. ADVANCES IN INFORMATION AND COMPUTER SECURITY, 2010, 6434 : 199 - +
  • [43] Runtime-based Behavior Dynamic Analysis System for Android Malware Detection
    Min, Luoxu
    Cao, Qinghua
    [J]. PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION APPLICATIONS (ICCIA 2012), 2012, : 233 - 236
  • [44] Efficient Dynamic Malware Analysis Based on Network Behavior Using Deep Learning
    Shibahara, Toshiki
    Yagi, Takeshi
    Akiyama, Mitsuaki
    Chiba, Daiki
    Yada, Takeshi
    [J]. 2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2016,
  • [45] Behavior-based Malware Analysis using Profile Hidden Markov Models
    Ravi, Saradha
    Balakrishnan, N.
    Venkatesh, Bharath
    [J]. PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON SECURITY AND CRYPTOGRAPHY (SECRYPT 2013), 2013, : 195 - 206
  • [46] Reinforcement learning-based detection method for malware behavior in industrial control systems
    Gao, Yang
    Wang, Li-Wei
    Ren, Wang
    Xie, Feng
    Mo, Xiao-Feng
    Luo, Xiong
    Wang, Wei-Ping
    Yang, Xi
    [J]. Gongcheng Kexue Xuebao/Chinese Journal of Engineering, 2020, 42 (04): : 455 - 462
  • [47] Malware Detection Method Based on Visualization
    Xie, Nannan
    Liang, Haoxiang
    Mu, Linyang
    Zhang, Chuanxue
    [J]. ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING, ICA3PP 2023, PT VI, 2024, 14492 : 252 - 264
  • [48] Design on Android malware behavior analysis system
    [J]. Li, J.-H. (jovistar@gmail.com), 1600, Beijing University of Posts and Telecommunications (37):
  • [49] Identifying DGA Malware via Behavior Analysis
    Zang, Xiaodong
    Gong, Jian
    Zong, Ping
    [J]. 2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2021,
  • [50] Behavior Analysis of Malware Using Machine Learning
    Dhammi, Arshi
    Singh, Maninder
    [J]. 2015 EIGHTH INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING (IC3), 2015, : 481 - 486