A novel classification approach for Android malware based on feature fusion and natural language processing

Author:

Chen Jinfu1,Zhao Zian1,Chen Xiao2,Cai Saihua1,Yin Shang1,Song Luo1

Affiliation:

1. School of Computer Science and Communication Engineering, Jiangsu University, China

2. University of Edinburgh, United Kingdom

Funder

National Natural Science Foundation of China

Publisher

ACM

Reference16 articles.

1. On-Device Detection of Repackaged Android Malware via Traffic Clustering;Gaofeng He;Security and Communication Networks

2. A survey of android application and malware hardening

3. [ 3 ] Li J , Yun X , Tian M , A method of HTTP malicious traffic detection on mobile networks //2019 IEEE Wireless Communications and Networking Conference (WCNC) . IEEE , 2019 : 1-8. [3] Li J, Yun X, Tian M, et al. A method of HTTP malicious traffic detection on mobile networks //2019 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2019: 1-8.

4. Improved mutual information measure for clustering, classification, and community detection

5. Detecting Android Malware Leveraging Text Semantics of Network Flows

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