공개 딥러닝 라이브러리에 대한 보안 취약성 검증
Vol. 29, No. 1, pp. 117-125,
1월.
2019
10.13089/JKIISC.2019.29.1.117, Full Text:
Keywords: Adversarial attack, MNIST, Deep Learning, Security, Autoencoder, Convolution Neural Network
Abstract Statistics
Cite this article
10.13089/JKIISC.2019.29.1.117, Full Text:
Keywords: Adversarial attack, MNIST, Deep Learning, Security, Autoencoder, Convolution Neural Network
Abstract Statistics
Cite this article
[IEEE Style]
정재한 and 손태식, "Security Vulnerability Verification for Open Deep Learning Libraries," Journal of The Korea Institute of Information Security and Cryptology, vol. 29, no. 1, pp. 117-125, 2019. DOI: 10.13089/JKIISC.2019.29.1.117.
[ACM Style]
정재한 and 손태식. 2019. Security Vulnerability Verification for Open Deep Learning Libraries. Journal of The Korea Institute of Information Security and Cryptology, 29, 1, (2019), 117-125. DOI: 10.13089/JKIISC.2019.29.1.117.