Results 21 to 30 of about 386,074 (314)
On the Possibility of Classical Client Blind Quantum Computing
Cryptography, 2021 Classical client remote state preparation (CC − RSP) is a primitive where a fully classical party (client) can instruct the preparation of a sequence of random quantum states on some distant party (server) in a way that the description is known to the ...
Alexandru Cojocaru +3 more
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Classical hardness of learning with errors [PDF]
Proceedings of the forty-fifth annual ACM symposium on Theory of Computing, 2013 Preliminary version in STOC ...
Zvika Brakerski +4 more
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Detecting Errors with Zero-Shot Learning
Entropy, 2022 Error detection is a critical step in data cleaning. Most traditional error detection methods are based on rules and external information with high cost, especially when dealing with large-scaled data.
Xiaoyu Wu, Ning Wang
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Learning with Physical Noise or Errors [PDF]
IEEE Transactions on Dependable and Secure Computing, 2020 Hard learning problems have recently attracted significant attention within the cryptographic community, both as a versatile assumption on which to build various protocols, and as a potentially sound basis for lightweight (possibly side-channel and fault resistant) implementations.
Dina Kamel +4 more
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New Constructions of Identity-Based Dual Receiver Encryption from Lattices
Entropy, 2020 Dual receiver encryption (DRE), being originally conceived at CCS 2004 as a proof technique, enables a ciphertext to be decrypted to the same plaintext by two different but dual receivers and becomes popular recently due to itself useful application ...
Yuan Liu +3 more
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A Mathematical Perspective on Post-Quantum Cryptography
Mathematics, 2022 In 2016, the National Institute of Standards and Technology (NIST) announced an open competition with the goal of finding and standardizing suitable algorithms for quantum-resistant cryptography.
Maximilian Richter +3 more
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Learning by Trial and Error [PDF]
Games and Economic Behavior, 2009 Abstract A player learns by trial and error if he occasionally tries out new strategies, rejecting choices that are erroneous in the sense that they do not lead to higher payoffs. In a game, however, strategies can become erroneous due to a change of behavior by someone else.
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Learning the Language of Error [PDF]
, 2015 We propose to harness Angluin’s \(L^*\) algorithm for learning a deterministic finite automaton that describes the possible scenarios under which a given program error occurs. The alphabet of this automaton is given by the user (for instance, a subset of the function call sites or branches), and hence the automaton describes a user-defined abstraction ...
Martin Chapman +5 more
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Implementing RLWE-based Schemes Using an RSA Co-Processor
Transactions on Cryptographic Hardware and Embedded Systems, 2018 We repurpose existing RSA/ECC co-processors for (ideal) lattice-based cryptography by exploiting the availability of fast long integer multiplication.
Martin R. Albrecht +5 more
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Learning the Language of Software Errors
Journal of Artificial Intelligence Research, 2020 We propose to use algorithms for learning deterministic finite automata (DFA), such as Angluin’s L* algorithm, for learning a DFA that describes the possible scenarios under which a given program error occurs. The alphabet of this automaton is given by the user (for instance, a subset of the function call sites or branches), and ...
Hana Chockler +3 more
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