๐ฎ
๐ฎ
The Ethereal
CryptoSolve: Towards a Tool for the Symbolic Analysis of Cryptographic Algorithms
September 21, 2022 ยท The Ethereal ยท ๐ International Symposium on Games, Automata, Logics and Formal Verification
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Dalton Chichester, Wei Du, Raymond Kauffman, Hai Lin, Christopher Lynch, Andrew M. Marshall, Catherine A. Meadows, Paliath Narendran, Veena Ravishankar, Luis Rovira, Brandon Rozek
arXiv ID
2209.10321
Category
cs.LO: Logic in CS
Cross-listed
cs.CR,
cs.SC
Citations
1
Venue
International Symposium on Games, Automata, Logics and Formal Verification
Last Checked
5 months ago
Abstract
Recently, interest has been emerging in the application of symbolic techniques to the specification and analysis of cryptosystems. These techniques, when accompanied by suitable proofs of soundness/completeness, can be used both to identify insecure cryptosystems and prove sound ones secure. But although a number of such symbolic algorithms have been developed and implemented, they remain scattered throughout the literature. In this paper, we present a tool, CryptoSolve, which provides a common basis for specification and implementation of these algorithms, CryptoSolve includes libraries that provide the term algebras used to express symbolic cryptographic systems, as well as implementations of useful algorithms, such as unification and variant generation. In its current initial iteration, it features several algorithms for the generation and analysis of cryptographic modes of operation, which allow one to use block ciphers to encrypt messages more than one block long. The goal of our work is to continue expanding the tool in order to consider additional cryptosystems and security questions, as well as extend the symbolic libraries to increase their applicability.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Logic in CS
๐ฎ
๐ฎ
The Ethereal
Safe Reinforcement Learning via Shielding
๐ฎ
๐ฎ
The Ethereal
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
๐ฎ
๐ฎ
The Ethereal
Heterogeneous substitution systems revisited
๐ฎ
๐ฎ
The Ethereal
Omega-Regular Objectives in Model-Free Reinforcement Learning
๐ฎ
๐ฎ
The Ethereal