Predicting the Impact of Android Malicious Samples Via Machine Learning

Author:

Lopes Archana,Dave Sakshi,Kane Yash

Publisher

Springer Singapore

Reference5 articles.

1. Bedford, Andrew, et al. “Andrana: Quick and accurate malware detection for android." International Symposium on Foundations and Practice of Security. Spring-er, Cham, 2016.

2. Sanz, Borja, et al. "MAMA: Manifest analysis for malware detection in Android." Cybernetics and Systems 44.6–7 (2013): 469–488.

3. A. Feizollah, N.B. Anuar, R. Salleh, G. SuarezTangil, S. Furnell, AndroDi-alysis: Analysis of Android Intent Effectiveness in MalwareDetection. Compute. Secur. 65, 121–134 (2017)

4. Z. Yuan, Y. Lu, Z. Wang, Y. Xue, Droid-Sec: Deep Learning in Android Malware Detection. Sigcomm 2014, 371–372 (2014)

5. Lifan Xu, Wei Wang, Marco A Alvarez, John Cavazos, and Dongping Zhang. Parallelization of shortest path graph kernels on multi-core cpus and gpus. Pro-ceedings of the Programmability Issues for Heterogeneous Multicores (MultiProg), Vienna, Austria, 2014

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