A Novel Dynamic Attack on Classical Ciphers Using an Attention-Based LSTM Encoder-Decoder Model

A Novel Dynamic Attack on Classical Ciphers Using an Attention-Based LSTM Encoder-Decoder Model

Information security has become an intrinsic part of data communication. Cryptanalysis using deep learning–based methods to identify weaknesses in ciphers has not been thoroughly studied. Recently, long short-term memory (LSTM) networks have shown promising performance in sequential data...

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Bibliographic Details
Main Authors: Ezat Ahmadzadeh, Hyunil Kim, Ongee Jeong, Inkyu Moon
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Cryptanalysis
classical ciphers
attention-based LSTM encoder-decoder
recurrent neural network
Online Access:https://ieeexplore.ieee.org/document/9408655/

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