Pietrzak, K.: Cryptography from learning parity with noise. In: Proceedings of the Theory and Practice of Computer Science (SOFTSEM 2012). pp. 99-114 (2012)K. Pietrzak, Cryptography from learning parity with noise, SOFSEM 2012: Theory and Practice of Computer Science, Lecture Notes in ...
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 provably secure means that the scheme comes with a proof...
Block ciphers represent an encryption method where blocks of data are encrypted with a deterministic algorithm using a symmetric key that has been securely exchanged. DES and AES are two popular examples of block ciphers. 2.3.1.2.1 Data Encryption Scheme (DES) Key size: 56 (+ 8 parity) bits...
Learning about Standard Cryptographic Algorithms Just why are there so many algorithms anyway? Why doesn’t the world just standardize on one algorithm? Given the large number of algorithms found in the field today, these are valid questions with no simple answers. At the most basic level, it’...
certain learning problem:第一种理解是'learning from parity with error' problem向高模的自然延伸;第二种理解是随机线性码的decoding问题 reduction:这种归约是量子的,解决学习问题的方法就意味着解决GapSVP、SIVP问题的量子算法 2. We also present a (classical) public-key cryptosystem whose security is based ...
Now, suppose we introduce a small amount of noise to our function, so that after multiplyingxanda, we add an error termeand reduce the whole thing modulo a (medium-sized) primeq. Then our noisy mystery function looks like Learning this noisy mystery function has been mathematically proven to...
“noisy” inner products of a secret vector with random vectors from uniform. The presumed hardness of this and the related learning parity with noise (LPN) problem has found many applications in cryptography. Its appeal stems from the fact that it is provably as hard as well studied worst-...
Dodis, Kalai and Lovett (STOC 2009) initiated the study of the Learning Parity with Noise (LPN) problem with (static) exponentially hard-to-invert auxiliary input. In particular, they showed that under a new assumption (called Learning Subspace with Noise) the above is quasi-polynomially hard...
This poses a barrier for building advanced cryptography from code-based assumptions such as Learning Parity with Noise (LPN), as LPN is only known to be in BPPSZK under an extremely low noise rate log2nn, for which it is broken in quasi-polynomial time. In this work, we propose ...
If the error rate is below the threshold, they remove any remaining errors from the rest of the raw key, to produce the reconciled key by using parity checks of subblocks of the tentative final key. To do this, they partition the key into blocks of length / such that each block is un...