Application of Deep Learning in Classification of Encrypted Images

Author:

Saxena Geetansh,Mishra Girish,Shrotriya Noopur

Publisher

Springer International Publishing

Reference15 articles.

1. Banik, S., Kumar Pandey, S., Peyrin, T., Sasaki, Y., Meng Sim, S., Todo, Y.: GIFT: A Small Present Towards Reaching the Limit of Lightweight Encryption (Full version) (n.d.). https://eprint.iacr.org/2017/622.pdf

2. Bansod, G., Pisharoty, N., Patil, A.: PICO: an ultra lightweight and low power encryption design for ubiquitous computing & electronic engineering. 18(3), 317–331 (2017). https://doi.org/10.1631/FITEE.1500415

3. Lecture Notes in Computer Science;A Bogdanov,2007

4. Daemen, J., Rijmen, V.: Note on naming Rijndael Note on naming (n.d.). https://csrc.nist.gov/CSRC/media/Projects/Cryptographic-Standards-and-Guidelines/documents/aes-development/Rijndael-ammended.pdf

5. Lazar, D., Chen, H., Wang, X., Zeldovich, N.: Why does cryptographic software fail? A case study and open problems (n.d.). http://lib.21h.io/library/3NAZDAR9/download/R6RTZ7MZ/Why_does_cryptographic_software_fail_-_A_case_study_and_open_problems_7p_.pdf

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1. Deep Learning for Classification of Encrypted Images;Lecture Notes in Networks and Systems;2023

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