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    PolarSig: An efficient digital signature based on polar codes

    , Article IET Communications ; Volume 14, Issue 17 , 2020 , Pages 2889-2897 Forghani, P ; KoochakShooshtari, M ; Aref, M. R ; Sharif University of Technology
    Institution of Engineering and Technology  2020
    Abstract
    Code-based digital signatures suffer from two main drawbacks: Large public key size and slow signature generation. Large public key size is inherent in almost all the code-based cryptosystems and other post-quantum alternatives; however, slow signature generation is due to their specific structure. Most of the current code-based signature schemes are constructed based on Courtois, Finiasz, and Sendrier (CFS) signature. CFS uses a counter to produce decodable syndromes or the complete decoding technique that imposes some extra computational cost to the signing algorithm for many choices of codes. In this study, the authors propose an efficient digital signature, PolarSig, which can reduce... 

    Multi variable-layer neural networks for decoding linear codes

    , Article 2020 Iran Workshop on Communication and Information Theory, IWCIT 2020, 26 May 2020 through 28 May 2020 ; August , 2020 Malek, S ; Salehkaleybar, S ; Amini, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    The belief propagation algorithm is a state of the art decoding technique for a variety of linear codes such as LDPC codes. The iterative structure of this algorithm is reminiscent of a neural network with multiple layers. Indeed, this similarity has been recently exploited to improve the decoding performance by tuning the weights of the equivalent neural network. In this paper, we introduce a new network architecture by increasing the number of variable-node layers, while keeping the check-node layers unchanged. The changes are applied in a manner that the decoding performance of the network becomes independent of the transmitted codeword; hence, a training stage with only the all-zero...