Cryptographic Algorithms Identification based on Deep Learning
Cryptographic Algorithms Identification based on Deep Learning
Ruiqi Xia 1, Manman Li 2 and Shaozhen Chen 2, 1 Information Engineering University, China, 2 Kexue Avenue, China
Abstract
The identification of cryptographic algorithms is the premise of cryptanalysis which can help recover the keys effectively. This paper focuses on the construction of cryptographic identification classifiers based on residual neural network and feature engineering. We select 6 algorithms including block ciphers and public keys ciphers for experiments. The results show that the accuracy is generally over 90% for each algorithm. Our work has successfully combined deep learning with cryptanalysis, which is also very meaningful for the development of modern cryptography and pattern recognition.
Keywords
Deep learning, Cryptography, Feature engineering, Residual neural network, Ciphers identification.
Full Text : https://aircconline.com/csit/papers/v...
Abstract URL : https://aircconline.com/csit/abstract...
Volume URL : https://airccse.org/csit/V12N12.html
#security #deeplearning #cryptography #featureengineering #residualneuralnetwork #ciphersidentification #machinelearning #artificialintelligence #patternrecognition
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