Transalg: a Tool for Translating Procedural Descriptions of Discrete Functions to SAT
In this paper we present the Transalg system, designed to produce SAT encodings for discrete functions, written as programs in a specific language. Translation of such programs to SAT is based on propositional encoding methods for formal computing models and on the concept of symbolic execution. We used the Transalg system to make SAT encodings for a number of cryptographic functions.
Code (0)
등록된 구현이 없습니다.
Tasks
TranslationSimilar Papers 제목 키워드 기반
Translation of Algorithmic Descriptions of Discrete Functions to SAT with Applications to Cryptanalysis Problems
In the present paper, we propose a technology for translating algorithmic descriptions of discrete functions to SAT. The proposed technology is aimed at applications in algebraic cryptanalysis. We describe how cryptanaly…
CryptanalysisTranslationEncoding Cryptographic Functions to SAT Using Transalg System
In this paper we propose the technology for constructing propositional encodings of discrete functions. It is aimed at solving inversion problems of considered functions using state-of-the-art SAT solvers. We implemented…
CryptanalysisDistributed ComputingProcedural Content Generation for GDL Descriptions of Simplified Boardgames
We present initial research towards procedural generation of Simplified Boardgames and translating them into an efficient GDL code. This is a step towards establishing Simplified Boardgames as a comparison class for Gene…
Arti-PG: A Toolbox for Procedurally Synthesizing Large-Scale and Diverse Articulated Objects with Rich Annotations
The acquisition of substantial volumes of 3D articulated object data is expensive and time-consuming, and consequently the scarcity of 3D articulated object data becomes an obstacle for deep learning methods to achieve r…
ObjectA Procedural Texture Generation Framework Based on Semantic Descriptions
Procedural textures are normally generated from mathematical models with parameters carefully selected by experienced users. However, for naive users, the intuitive way to obtain a desired texture is to provide semantic …
Multi-Label LearningTexture Synthesis