BRISK: Dynamic Encryption Based Cipher for Long Term Security. [PDF]
Sensors (Basel), 2021 Dwivedi AD.
europepmc +1 more source
Застосування кубічних тестрів у криптоаналізі симетричних шифрів [PDF]
, 2018 Дипломну роботу виконано на 81 аркуші, вона містить 2 додатки та перелік посилань на використані джерела із 35 найменувань. У роботі наведено 7 рисунків та 10 таблиць.
Свічкарьов, Іван Володимирович
core
Pen and Paper Arguments for SIMON and SIMON-like Designs [PDF]
, 2016 In this work, we analyze the resistance of SIMON-like ciphers against differential attacks without using computer-aided methods. In this context, we first define the notion of a SIMON-like cipher as a generalization of the SIMON design.
Christof Beierle
core
An Automated Model to Search For Differential Meet-In-The-Middle Attack: Applications to AndRX Ciphers [PDF]
Differential meet-in-the-middle (MITM) cryptanalysis, recently introduced by Boura et al., has emerged as a powerful and versatile technique for assessing the security of modern block cipher designs.
Debasmita Chakraborty +3 more
core
A Multi-Differential Approach to Enhance Related-Key Neural Distinguishers [PDF]
At CRYPTO 2019, Gohr pioneered the integration of differential cryptanalysis with neural networks, demonstrating significant advantages over traditional distinguishers. Subsequently, at Inscrypt 2020, Su et al.
Qichun Wang, Xue Yuan
core
On the Design Rationale of SIMON Block Cipher: Integral Attacks and Impossible Differential Attacks against SIMON Variants [PDF]
, 2016 SIMON is a lightweight block cipher designed by NSA in 2013. NSA presented the specification and the implementation efficiency, but they did not provide detailed security analysis nor the design rationale. The original SIMON has rotation constants of $(1,
Kota Kondo, Tetsu Iwata, Yu Sasaki
core
Improving Differential-Neural Distinguisher For Simeck Family [PDF]
In CRYPTO 2019, Gohr introduced the method of differential neural cryptanalysis, utilizing neural networks as the underlying distinguishers to achieve distinguishers for (5-8)-round of the Speck32/64 cipher and subsequently recovering keys for 11 and 12 ...
Qichun Wang, Xue Yuan
core
FPGA Modeling and Optimization of a SIMON Lightweight Block Cipher. [PDF]
Sensors (Basel), 2019 Abed S, Jaffal R, Mohd BJ, Alshayeji M.
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Comparison between dobutamine echocardiography and thallium-201 scintigraphy in detecting residual stenosis, ischemia, and necrosis in patients with prior myocardial infarction. [PDF]
Clin Cardiol, 1997 Macieira-Coelho E +6 more
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Generic Partial Decryption as Feature Engineering for Neural Distinguishers [PDF]
In Neural Cryptanalysis, a deep neural network is trained as a cryptographic distinguisher between pairs of ciphertexts $(F(X), F(X \oplus \delta))$, where $F$ is either a random permutation or a block cipher, $\delta$ is a fixed difference.
Anna Hambitzer +4 more
core