Malicious Code Detection based on Image Processing Using Deep Learning

Author:

Kumar Rajesh1,Xiaosong Zhang1,Khan Riaz Ullah1,Ahad Ijaz1,Kumar Jay2

Affiliation:

1. University of Electronic Science and Technology of China

2. Quaid-e-Azam University Islamabad, Pakistan

Publisher

ACM Press

Reference12 articles.

1. Vision reseach lab malimg dataset http://old.vision.ece.ucsb.edu/spam/malimg.shtml.

2. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M. and Ghemawat, S., 2016. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467.

3. Adebayo, O.S. and Aziz, N.A., 2015. Static Code Analysis of Permission-based Features for Android Malware Classification Using Apriori Algorithm with Particle Swarm Optimization. Journal of Information Assurance & Security, 10(4).

4. Alme, C., Mcafee, Inc., 2012. Systems, apparatus, and methods for detecting malware. U.S. Patent 8,312,546.

5. Bennasar, H., Bendahmane, A. and Essaaidi, M., 2017, April. An Overview of the State-of-the-Art of Cloud Computing Cyber-Security. In International Conference on Codes, Cryptology, and Information Security (pp. 56--67). Springer, Cham.

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