learning parity with noise 意思是：学习与噪声等值
learning parity with noise原理 Learning parity with noise (LPN) is a cryptographic problem that involves learning a secret vector known as the "parity bit" even when the communication is noisy. The problem assumes a communication channel that introduces random errors, making it challenging to ...
如果你年纪比较大,比如年纪比我大的话,你可能会知道一个困难问题,叫做Learning Parity with Noise问题。这个问题在1980年得到了些许关注,这是我能找到的最早的参考文献了,可能这个问题的提出时间要更早。密码学界对这个问题进行了一些研究,不过没研究多少。这几年,这个问题及其衍生问题有复苏的趋势。我想其中的原因是...
Commitments and Efficient Zero-Knowledge Proofs from Learning Parity with Noise We construct a perfectly binding string commitment scheme whose security is based on the learning parity with noise (LPN) assumption, or equivalently, the hardness of decoding random linear codes. Our A Jain,S Krenn,K ...
The Learning Parity with Noise (LPN) problem has recently found many applications in cryptography as the hardness assumption underlying the constructions of “provably secure” cryptographic schemes like encryption or authentication protocols. Being...
The linearity scheme is based on learning parity with noise. The method includes discovering a linearity relationship between the first and the second linearity ciphertexts. The method includes receiving a first and a second proximity hash value representative of the first and second biometric templates...
The Learning Parity with Noise (LPN) problem is well understood in learning theory and cryptography and has been found quite useful in constructing various lightweight cryptographic primitives. There exists non-trivial evidence that the problem is robust on high-entropy secrets (and even given hard-...
专利名称：LEARNING PARITY WITH NOISE-BASED RELATIONAL ENCRYPTION FOR PROXIMITY RELATIONS 发明人：Avradip MANDAL,Arnab ROY,Hart MONTGOMERY 申请号：US15144713 申请日：20160502 公开号：US20170085379A1 公开日：20170323 专利内容由知识产权出版社提供 专利附图：摘要：A method includes receiving a first and a ...
摘要 The Learning Parity with Noise (LPN) problem is well understood in learning theory and cryptography and has been foun... 出版源 Springer International Publishing , 2016 关键词 Learning Parity with Noise / H...
Learning parity with noise. Let \({\varvec{s}} \in \{0,1\}^n\) be a secret vector and let \(\eta \in [0,1/2)\) be a noise parameter. An LPN sample is given by $$\begin{aligned} ({\varvec{x}}, \left<{\varvec{s}},{\varvec{x}}\right> + e \bmod 2) \in \...