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We construct a strong extractor against quantum storage that works for every min-entropy $k$, has logarithmic seed length, and outputs $\Omega(k)$ bits, provided that the quantum adversary has at most $\beta k$ qubits of memory, for any…

Quantum Physics · Physics 2011-06-24 Avraham Ben-Aroya , Amnon Ta-Shma

In a recent breakthrough \cite{CZ15}, Chattopadhyay and Zuckerman gave an explicit two-source extractor for min-entropy $k \geq \log^C n$ for some large enough constant $C$. However, their extractor only outputs one bit. In this paper, we…

Computational Complexity · Computer Science 2015-08-06 Xin Li

Privacy amplification is the task by which two cooperating parties transform a shared weak secret, about which an eavesdropper may have side information, into a uniformly random string uncorrelated from the eavesdropper. Privacy…

Quantum Physics · Physics 2017-09-05 Gil Cohen , Thomas Vidick

This paper investigates the privacy amplification problem, and compares the existing two bounds: the exponential bound derived by one of the authors and the min-entropy bound derived by Renner. It turns out that the exponential bound is…

Information Theory · Computer Science 2012-11-26 Shun Watanabe , Masahito Hayashi

Nonlinear aggregation is central to modern distributed systems, yet its privacy behavior is far less understood than that of linear aggregation. Unlike linear aggregation where mature mechanisms can often suppress information leakage,…

Signal Processing · Electrical Eng. & Systems 2026-01-21 Wenrui Yu , Jaron Skovsted Gundersen , Richard Heusdens , Qiongxiu Li

We study the problem of constructing multi-source extractors in the quantum setting, which extract almost uniform random bits against quantum side information collected from several initially independent classical random sources. This is a…

Quantum Physics · Physics 2014-11-11 Kai-Min Chung , Xin Li , Xiaodi Wu

Privacy amplification is a necessary step in all quantum key distribution protocols, and error correction is needed in each except when signals of many photons are used in the key communication in quantum noise approach. No security…

Quantum Physics · Physics 2014-11-11 Horace Yuen

Privacy and communication constraints are two major bottlenecks in federated learning (FL) and analytics (FA). We study the optimal accuracy of mean and frequency estimation (canonical models for FL and FA respectively) under joint…

Machine Learning · Statistics 2023-04-05 Wei-Ning Chen , Dan Song , Ayfer Ozgur , Peter Kairouz

The exponential growth of data collection necessitates robust privacy protections that preserve data utility. We address information disclosure against adversaries with bounded prior knowledge, modeled by an entropy constraint $H(X) \geq…

Cryptography and Security · Computer Science 2026-03-27 Genqiang Wu , Xiaoying Zhang , Yu Qi , Hao Wang , Jikui Wang , Yeping He

Post-processing of the raw bits produced by a true random number generator (TRNG) is always necessary when the entropy per bit is insufficient for security applications. In this paper, we derive a tight bound on the output min-entropy of…

Cryptography and Security · Computer Science 2024-06-25 Miloš Grujić , Ingrid Verbauwhede

We examine the task of privacy amplification from information-theoretic and coding-theoretic points of view. In the former, we give a one-shot characterization of the optimal rate of privacy amplification against classical adversaries in…

Information Theory · Computer Science 2018-11-26 Joseph M. Renes

We prove an achievability result for privacy amplification and decoupling in terms of the sandwiched R\'enyi entropy of order $\alpha \in (1,2]$; this extends previous results which worked for $\alpha=2$. The fact that this proof works for…

Quantum Physics · Physics 2022-01-11 Frédéric Dupuis

This paper studies the design of an optimal privacyaware estimator of a public random variable based on noisy measurements which contain private information. The public random variable carries non-private information, however, its estimate…

Optimization and Control · Mathematics 2018-08-08 Ehsan Nekouei , Henrik Sandberg , Mikael Skoglund , Karl H. Johansson

We present an improved $(\epsilon, \delta)$-jointly differentially private algorithm for packing problems. Our algorithm gives a feasible output that is approximately optimal up to an $\alpha n$ additive factor as long as the supply of each…

Data Structures and Algorithms · Computer Science 2019-05-03 Zhiyi Huang , Xue Zhu

We explicitly construct the first nontrivial extractors for degree $d \ge 2$ polynomial sources over $\mathbb{F}_2^n$. Our extractor requires min-entropy $k\geq n - \tilde{\Omega}(\sqrt{\log n})$. Previously, no constructions were known,…

Computational Complexity · Computer Science 2024-02-02 Eshan Chattopadhyay , Jesse Goodman , Mohit Gurumukhani

The extraction of randomness from weakly random seeds is a problem of central importance with multiple applications. In the device-independent setting, this problem of quantum randomness amplification has been mainly restricted to specific…

Quantum Physics · Physics 2023-04-20 Ravishankar Ramanathan

We study quantum soft covering and privacy amplification against quantum side information. The former task aims to approximate a quantum state by sampling from a prior distribution and querying a quantum channel. The latter task aims to…

Quantum Physics · Physics 2022-02-24 Yu-Chen Shen , Li Gao , Hao-Chung Cheng

Secure distributed data compression in the presence of an eavesdropper is explored. Two correlated sources that need to be reliably transmitted to a legitimate receiver are available at separate encoders. Noise-free, limited rate links from…

Information Theory · Computer Science 2016-11-17 Deniz Gunduz , Elza Erkip , H. Vincent Poor

The max-relative entropy together with its smoothed version is a basic tool in quantum information theory. In this paper, we derive the exact exponent for the asymptotic decay of the small modification of the quantum state in smoothing the…

Quantum Physics · Physics 2023-06-02 Ke Li , Yongsheng Yao , Masahito Hayashi

We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractors, which are extractors that remain…

Computational Complexity · Computer Science 2026-05-11 Farzan Byramji , Daniel M. Kane , Jackson Morris , Anthony Ostuni