2 citations · 2 across the 3 of their papers we have counts for
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cs.CR2025
Neural-Inspired Advances in Integral Cryptanalysis
Liu Zhang, Yiran Yao, Danping Shi +3
The study by Gohr et.al at CRYPTO 2019 and sunsequent related works have shown that neural networks can uncover previously unused features, offering novel insights into cryptanalys…
cs.CR2023
Improved Differential-neural Cryptanalysis for Round-reduced Simeck32/64
Liu Zhang, Jinyu Lu, Zilong Wang +1
In CRYPTO 2019, Gohr presented differential-neural cryptanalysis by building the differential distinguisher with a neural network, achieving practical 11-, and 12-round key recover…
cs.CR2022★ 2 cited
Improving Differential-Neural Distinguisher Model For DES, Chaskey, and PRESENT
Liu Zhang, Zilong Wang
In CRYPTO'19, Gohr proposed a new cryptanalysis strategy using machine learning algorithms. Combining the differential-neural distinguisher with a differential path and integrating…