Pages that link to "Item:Q2304981"
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The following pages link to Improving attacks on round-reduced Speck32/64 using deep learning (Q2304981):
Displaying 16 items.
- deep_speck (Q46287) (← links)
- Subsampling and knowledge distillation on adversarial examples: new techniques for deep learning based side channel evaluations (Q832386) (← links)
- A deeper look at machine learning-based cryptanalysis (Q2056717) (← links)
- Improved differential-linear attack with application to round-reduced Speck32/64 (Q2096647) (← links)
- Differential-ML distinguisher: machine learning based generic extension for differential cryptanalysis (Q2146092) (← links)
- Computing expected differential probability of (truncated) differentials and expected linear potential of (multidimensional) linear hulls in SPN block ciphers (Q2152038) (← links)
- MILP based differential attack on round reduced WARP (Q2154058) (← links)
- Enhancing differential-neural cryptanalysis (Q6135401) (← links)
- Panther: a sponge based lightweight authenticated encryption scheme (Q6157571) (← links)
- Linear Attack on Round-Reduced DES Using Deep Learning (Q6485978) (← links)
- Meet-in-the-filter and dynamic counting with applications to \textsc{Speck} (Q6535077) (← links)
- Improved differential cryptanalysis on SPECK using plaintext structures (Q6535474) (← links)
- More insight on deep learning-aided cryptanalysis (Q6595824) (← links)
- CLAASP: a cryptographic library for the automated analysis of symmetric primitives (Q6620060) (← links)
- Deep learning-based rotational-XOR distinguishers for AND-RX block ciphers: evaluations on Simeck and Simon (Q6620063) (← links)
- Is ML-based cryptanalysis inherently limited? Simulating cryptographic adversaries via gradient-based methods (Q6652981) (← links)
