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milp-tool-for-cryptanalysis-of-block-ciphers

This tool is able to construct the MILP model for some bit-oriented block ciphers. once you describe the block-cipher on it, you can do differential and linear cryptanalysis on it. It is also suitable to find impossible input and output, which helps you in impossible differential attack, and zero-correlation attack. The MILP models are based on Gurobi format. In the link (https://drive.google.com/open?id=1VkDEjezc8PJR6m0JA8kaizTNV4IjLT1W ) you can see how the tool works

milp-warp-milp

MILP Based Differential Characteristics Search for Block Cipher WARP

milp_conditional_cube_attack

Materials of "Improved Conditional Cube Attacks on Keccak Key Modes with MILP Method".

milp_division_property

Applying MILP Method to Searching Integral Distinguishers Based on Division Property for 6 Lightweight Block Ciphers

milp_division_property-1

milp_divisionproprerty_linearlayer

Code for the paper "On MILP-based Automatic Search for Bit-Based Division Property for Ciphers with (large) Linear Layers", ACISP 2021

milp_improved-differential-attacks-on-snow-v-snow-vi

Improved-differential-attacks-on-SNOW-V-SNOW-Vi

milp_speck

milpbasedsearchalgorithmdiff

new============Code for FSE 2020 - Improving the MILP-based Security Evaluation Algorithm against Differential-Linear Cryptanalysis Using A Divide-and-Conquer Approach

minisat

A minimalistic and high-performance SAT solver

ml-block-cipher

nd_an-assessment-of-differential-neural-distinguishers

nd_differential-ml-distinguisher

Source Code for Differential-ML Distinguisher

nd_improved-neural-distinguishers-with-multi-round-and-multi-splicing-construct

The code is related to 'Improved Neural Distinguishers with Multi-Round and Multi-Splicing Construction',

nd_improved-related-key-differential-based-neural-distinguishers

nd_multiple-ciphertext-pairs

A new neural distinguisher considering features derived from multiple ciphertext pairs

nd_speck32_simon32

Supplementary code and data to the paper entitled "Enhancing Differential-Neural Cryptanalysis"

ndd--deep_learning_vs_conventional_distinguishers

Implementation of 2 conventional and 2 deep learning based distinguishers

ndd-cryptanalysis-using-deep-neural-networks

We have proposed the optimized deep neural network approach for cryptanalysis of symmetric encryption algorithm 64-bit DES (Data encryption standard). Our approach has used backpropagation techniques with multiple hidden layers and advanced activation functions also we have addressed the problem of vanishing gradient. Further, the implementation results show that we have achieved 90% accuracy which is significantly higher as compared to previous approaches.

ndd-neural-aided-statistical-attack-for-cryptanalysis

Neural Aided Statistical Attack for Cryptanalysis

ndd-simon-speck-neural_distinguisher

Neural distinguisher of reduced round Speck 32/64+simon

neuraldistingsuisherwithinception

neurocore-public

NeuroCore: Guiding CDCL with Unsat-Core Predictions

neurosat

NeuroSAT: Learning a SAT Solver from Single-Bit Supervision

nid-integral-neural-distinguisher

Integral Neural-Distinguisher

noveljava

java开发的小说爬虫，ssm框架搭建web展示

partystudy

掌上党建移动端和发布端

peigen

An open source project for study S-boxes

pipo-milp

MILP Based Differential Characteristics Search for Lightweight Block Cipher PIPO

pptsource

python阶段PPT课件详细整理内容