Titlebook: Computer Security – ESORICS 2023; 28th European Sympos Gene Tsudik,Mauro Conti,Georgios Smaragdakis Conference proceedings 2024 The Editor(

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Making an Asymmetric PAKE Quantum-Annoying by Hiding Group Elements security properties, but has the drawback of being vulnerable to quantum adversaries due to its reliance on discrete logarithm-based building blocks: solving a single discrete logarithm allows the attacker to perform an offline dictionary attack and recover the password. We show how to modify KHAPE

鉆孔

Commitments with?Efficient Zero-Knowledge Arguments from?Subset Sum Problemsthat these .-complete problems provide post-quantum security contrary to the number theory assumptions currently used in cryptography. Using techniques recently introduced by Feneuil, Maire, Rivain and Vergnaud, this simple commitment scheme enables an efficient zero-knowledge proof of knowledge for

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神刊

Secure Outsourced Matrix Multiplication with?Fully Homomorphic Encryptiononments. This capability allows for the outsourcing of computational tasks, effectively addressing security and privacy concerns. This paper studies the secure matrix multiplication problem, a fundamental operation used in various outsourced computing applications such as statistical analysis and ma

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Sequential Half-Aggregation of?Lattice-Based Signaturesith Aborts (Lyubashevsky, Asiacrypt’09) blueprint, . can be seen as an optimized version of the GPV-paradigm (Gentry et al., STOC’06). An important question now is whether those signatures allow additional features such as the aggregation of distinct signatures. One example are sequential aggregate

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Kernel

Cheap and?Fast Iterative Matrix Inverse in?Encrypted Domaind data. However, due to the limitations of arithmetic HE schemes, which typically only support addition and multiplication, many nonlinear operations must be approximated using these basic operations. As a result, some nonlinear operations cannot be executed in the same manner as they would be in th

Myelin

Practical Randomized Lattice Gadget Decomposition with?Application to?FHEomized following a subgaussian distribution, it is called subgaussian (gadget) decomposition which guarantees that we can bound the noise contained in ciphertexts by its variance. This gives tighter and cleaner noise bound in average case, instead of the use of its norm. Even though there are few at