Author:
Vu Thanh Nguyen,Nguyen Toan Tan,Phan Trung Hieu,Do Duy Thao,Van Ke Hoang,Le Tuan Dinh
Publisher
Springer International Publishing
Reference12 articles.
1. Symantec Corporation: Detecting Complex Viruses.
https://www.symantec.com/connect/articles/detecting-complex-viruses
. Accessed 10 June 2017
2. AV-TEST Institute: The AV-TEST Security Report, Magdeburg (2016)
3. Schultz, M.G., Eleazar, E., Erez, Z., Salvatore, S.J.: Data mining methods for detection of new malicious executables. In: IEEE Symposium Security and Privacy, S&P 2001, Proceedings, pp. 38–49 (2001)
4. Kolter, J.Z., Maloof, M.A.: Learning to detect and classify malicious executables in the wild. J. Mach. Learn. Res. 7, 2721–2744 (2006)
5. Yuan, Z., Lu, Y., Xue, Y.: Droiddetector: android malware characterization and detection using deep learning. Tsinghua Sci. Technol. 21(1), 114–123 (2016)
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