Results 11 to 20 of about 1,743,904 (288)
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
doaj +3 more sources
Multifractal analysis of perceptron learning with errors [PDF]
Physical Review E, 1997 Random input patterns induce a partition of the coupling space of a perceptron into cells labeled by their output sequences. Learning some data with a maximal error rate leads to clusters of neighboring cells. By analyzing the internal structure of these
A. Engel +14 more
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On the concrete hardness of Learning with Errors
Journal of Mathematical Cryptology, 2015 The learning with errors (LWE) problem has become a central building block of modern cryptographic constructions. This work collects and presents hardness results for concrete instances of LWE.
Albrecht Martin R. +2 more
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Learning with Errors is easy with quantum samples
, 2018 Learning with Errors is one of the fundamental problems in computational learning theory and has in the last years become the cornerstone of post-quantum cryptography.
Grilo, Alex B. +2 more
core +3 more sources
An overview of torus fully homomorphic encryption [PDF]
International Journal of Group Theory, 2023 The homomorphic encryption allows us to operate on encrypted data, making any action less vulnerable to hacking. The implementation of a fully homomorphic cryptosystem has long been impracticable. A breakthrough was achieved only in 2009 thanks to Gentry
Maria Ferrara +2 more
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Fully Dynamic Multi-Key FHE Without Gaussian Noise
IEEE Access, 2021 Fully dynamic multi-key fully homomorphic encryption (FHE) that allows an unlimited number of homomorphic operations for unconstrained parties. That is to say, it supports performing as many computational procedures on inputs (which are encrypted by an ...
Yu Huang, Kaigui Wu, Ming Chen
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The polynomial learning with errors problem and the smearing condition
Journal of Mathematical Cryptology, 2022 As quantum computing advances rapidly, guaranteeing the security of cryptographic protocols resistant to quantum attacks is paramount. Some leading candidate cryptosystems use the learning with errors (LWE) problem, attractive for its simplicity and ...
Babinkostova Liljana +4 more
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Leveled Fully Homomorphic Signcryption From Lattices
IEEE Access, 2023 With the continuous and rapid development of Cloud Computing, Big Data and Internet of Things, it is extremely critical to protect data with homomorphism, privacy and integrity. For this, Rezaeibagha et al.
Xiaodan Jin +4 more
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When Bad News Become Good News
Transactions on Cryptographic Hardware and Embedded Systems, 2022 Hard physical learning problems have been introduced as an alternative option to implement cryptosystems based on hard learning problems. Their high-level idea is to use inexact computing to generate erroneous computations directly, rather than to first
Davide Bellizia +4 more
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Star-Specific Key-Homomorphic PRFs From Learning With Linear Regression
IEEE Access, 2023 We introduce a novel method to derandomize the learning with errors (LWE) problem by generating deterministic yet sufficiently independent LWE instances that are constructed by using linear regression models, which are generated via (wireless ...
Vipin Singh Sehrawat +2 more
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