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참고문헌 (11)

1. 딥 러닝, https://ko.wikipedia.org/wiki/딥_러닝, 2018.1 

2. A. NG, "How Scale is Enabling Deep Learning", https://www.youtube.com/watch?vLcfLo7YP8O4, 2016.2. 

3. K. Lee and M. Son, "Deepspotcloud: leveraging cross-region GPU spot instances for deep learning," IEEE Cloud'17 

4. A. Kantchelian 외 7명, "Better Malware Ground Truth: Techniques for Weighting Anti-Virus Vendor Labels," ACM AISec'15 

5. 정지만, 홍성현, 김영재, 명준우, 정성민, 이진우, 김준호, 윤명근, "4차 산업혁명을 대비한 딥러닝 기술의 금융보안 적용 연구", 금융정보보호공모전 최우수논문상 2017 

6. N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, R. Salakhutdinov "Dropout: A Simple Way to Prevent Neural Networks from Overfitting", Journal of Machine Learning Research, 2014 

7. X. Hu , S. Bhatkar, K. Griffin, K. G. Shin, "MutantX-S: Scalable Malware Clustering Based on Static Features," USENIX ATC'13 

8. J. Saxe and K. Berlin, "Deep Neural Network Based Malware Detection Using Two Dimensional Binary Program Features," IEEE Malware'15 

9. Microsoft Malware Classification Challenge (BIG 2015), https://www.kaggle.com/c/malware-classification. 

10. I. Goodfellow, J. Shlens, and C. Szegedy, "Explaining and Harnessing Adversarial Examples," ICLR'15 

11. Q. Wang 외 6인, "Adversary Resistant Deep Neural Networks with an Application to Malware Detection," KDD'17