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This paper studies the limitations of the generic approaches to solving cryptographic problems in classical and quantum settings in various models. - In the classical generic group model (GGM), we find simple alternative proofs for the…

Quantum Physics · Physics 2024-02-20 Minki Hhan

Nowadays, predominant asymmetric cryptographic schemes are considered to be secure because discrete logarithms are believed to be hard to be computed. The algorithm of Shor can effectively compute discrete logarithms, i.e. it can brake such…

Cryptography and Security · Computer Science 2025-04-01 Johanna Barzen , Frank Leymann

In this paper, we study the Empirical Risk Minimization (ERM) problem in the non-interactive Local Differential Privacy (LDP) model. Previous research on this problem \citep{smith2017interaction} indicates that the sample complexity, to…

Machine Learning · Computer Science 2020-11-12 Di Wang , Marco Gaboardi , Adam Smith , Jinhui Xu

This paper aims to determine the exact success probability at each step of Shor's algorithm. Although the literature usually provides a lower bound on this probability, we present an improved bound. The derived formulas enable the…

Quantum Physics · Physics 2025-06-17 Ali Abbassi , Lionel Bayle

Difficulty of calculation of discrete logarithm for any arbitrary Field is the basis for security of several popular cryptographic solutions. Pohlig-Hellman method is a popular choice to calculate discrete logarithm in finite field $F_p^*$.…

Number Theory · Mathematics 2021-04-30 Rajeev Kumar

This paper presents algorithms for local inversion of maps and shows how several important computational problems such as cryptanalysis of symmetric encryption algorithms, RSA algorithm and solving the elliptic curve discrete log problem…

Cryptography and Security · Computer Science 2022-03-08 Virendra Sule

The discrete logarithm problem in a finite group is the basis for many protocols in cryptography. The best general algorithms which solve this problem have time complexity of $\mathcal{O}(\sqrt{N}\log N)$, and a space complexity of…

Computational Complexity · Computer Science 2022-03-16 Simran Tinani , Joachim Rosenthal

Diffie-Hellman key-agreement and RSA cryptosystem are widely used to provide security in internet protocols. But both of the two algorithms are totally breakable using Shor's algorithms. This paper proposes two connected matrix-based…

Cryptography and Security · Computer Science 2022-08-05 Abdelhaliem Babiker

Quantum computers have the potential to perform computational tasks beyond the reach of classical machines. A prominent example is Shor's algorithm for integer factorization and discrete logarithms, which is of both fundamental importance…

Finding efficient, easily implementable differentially private (DP) algorithms that offer strong excess risk bounds is an important problem in modern machine learning. To date, most work has focused on private empirical risk minimization…

Machine Learning · Computer Science 2024-09-23 Andrew Lowy , Meisam Razaviyayn

In this paper, we initiate a systematic investigation of differentially private algorithms for convex empirical risk minimization. Various instantiations of this problem have been studied before. We provide new algorithms and matching lower…

Machine Learning · Computer Science 2014-10-21 Raef Bassily , Adam Smith , Abhradeep Thakurta

In late 2012 and early 2013 the discrete logarithm problem (DLP) in finite fields of small characteristic underwent a dramatic series of breakthroughs, culminating in a heuristic quasi-polynomial time algorithm, due to Barbulescu, Gaudry,…

Number Theory · Mathematics 2014-06-13 Robert Granger , Thorsten Kleinjung , Jens Zumbrägel

In this paper, a new algorithm to solve the discrete logarithm problem is presented which is similar to the usual baby-step giant-step algorithm. Our algorithm exploits the order of the discrete logarithm in the multiplicative group of a…

Cryptography and Security · Computer Science 2020-11-17 Prabhat Kushwaha , Ayan Mahalanobis

Too often, quantum computer scientists seek to create new algorithms entirely fresh from new cloth when there are extensive and optimized classical algorithms that can be generalized wholesale. At the same time, one may seek to maintain…

Quantum Physics · Physics 2025-09-04 Lucas T. Brady , Stuart Hadfield

Given an empirical distribution $f(x)$ of sensitive data $x$, we consider the task of minimizing $F(y) = D_{\text{KL}} (f(x)\Vert y)$ over a probability simplex, while protecting the privacy of $x$. We observe that, if we take the…

Cryptography and Security · Computer Science 2023-02-23 Donlapark Ponnoprat

Group-based cryptography is a relatively unexplored family in post-quantum cryptography, and the so-called Semidirect Discrete Logarithm Problem (SDLP) is one of its most central problems. However, the complexity of SDLP and its…

Cryptography and Security · Computer Science 2024-06-10 Christopher Battarbee , Delaram Kahrobaei , Ludovic Perret , Siamak F. Shahandashti

For $q$ a prime power, the discrete logarithm problem (DLP) in $\mathbb{F}_{q}$ consists in finding, for any $g \in \mathbb{F}_{q}^{\times}$ and $h \in \langle g \rangle$, an integer $x$ such that $g^x = h$. We present an algorithm for…

Number Theory · Mathematics 2020-08-25 Robert Granger , Thorsten Kleinjung , Jens Zumbrägel

We give precise quantum resource estimates for Shor's algorithm to compute discrete logarithms on elliptic curves over prime fields. The estimates are derived from a simulation of a Toffoli gate network for controlled elliptic curve point…

Quantum Physics · Physics 2017-11-01 Martin Roetteler , Michael Naehrig , Krysta M. Svore , Kristin Lauter

In this paper, we describe the randomized QLP (RQLP) algorithm and its enhanced version (ERQLP) for computing the low rank approximation to $A$ of size $m\times n$ efficiently such that $A\approx QLP$, where $L$ is the rank-$k$…

Numerical Analysis · Mathematics 2018-11-26 Nianci Wu , Hua Xiang

We study differentially private (DP) algorithms for stochastic convex optimization: the problem of minimizing the population loss given i.i.d. samples from a distribution over convex loss functions. A recent work of Bassily et al. (2019)…

Machine Learning · Computer Science 2020-05-12 Vitaly Feldman , Tomer Koren , Kunal Talwar