Description
We focus on two new number-theoretic problems of major importance for RSA and factoring-based cryptosystems. An RSA key generator Gen(1^k) = (n, e) is malleable when factoring n is easier when given access to a factoring oracle for other keys (n', e')!= (n, e) output by Gen. Gen is instance-malleable when it is easier to extract e-th roots mod n given an e'-th root extractor mod n' for (n', e') != (n , e) output by Gen. Instance-non-malleable generators are of prime importance for practical RSA-based systems (RSA-PSS, RSA-OAEP, etc) because their security can be shown not to be equivalent to RSA in the standard model, in contradiction with the random oracle heuristic. We investigate the malleability and instance-malleability of popular RSA key generators such as textbook RSA and low-exponent RSA and question the existence of non-trivial malleable RSA instances.
Next sessions
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Dissecting CRAFT, a full-round attack
Speaker : Eran Lambooij - Inria
I will present the first full-round key recovery attack on CRAFT, a block cipher introduced at ToSC 2019. The attack builds on the previous observation (ToSC 2026) that the state of CRAFT can be decomposed into two parts that barely exchange information. We transform this property into a dissection attack on the full-round cipher. This shows that in some cases we can elevate the dissection attack[…]-
Cryptography
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Key Attack on the ACDGV Matrix Encryption Scheme
Speaker : Anmoal Porwal - Technical University of Munich
I will present our key-recovery attack on the ACDGV public-key encryption scheme proposed at ASIACRYPT 2024 by Aragon, Couvreur, Dyseryn, Gaborit, and Vinçotte. The secret key is a Gabidulin code hidden by appending random rows and columns and by left- and right-multiplication with invertible matrices. Our attack exploits the resulting algebraic structure to recover an equivalent secret key. It[…]-
Cryptography
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Asymmetric primitive
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Module Learning With Errors and Structured Extrapolated Dihedral Cosets
Speaker : Jinwei Zheng - Télécom Paris
The Module Learning With Errors (MLWE) problem is the fundamental hardness assumption underlying the key encapsulation and signature schemes ML-KEM and ML-DSA, which have been selected by NIST for post-quantum cryptography standardization. Understanding its quantum hardness is crucial for assessing the security of these standardized schemes. Inspired by the equivalence between LWE and[…]-
Cryptography
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