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Metric Differential Privacy (mDP) extends the local differential privacy (LDP) framework to metric spaces, enabling more nuanced privacy protection for data such as geo-locations. However, existing mDP optimization methods, particularly…

Cryptography and Security · Computer Science 2025-09-11 Ruiyao Liu , Chenxi Qiu

A fundamental result in differential privacy states that the privacy guarantees of a mechanism are preserved by any post-processing of its output. In this paper we investigate under what conditions stochastic post-processing can amplify the…

Machine Learning · Computer Science 2019-10-29 Borja Balle , Gilles Barthe , Marco Gaboardi , Joseph Geumlek

Quantum continuous variables are being explored as an alternative means to implement quantum key distribution, which is usually based on single photon counting. The former approach is potentially advantageous because it should enable higher…

Quantum Physics · Physics 2009-11-10 F. Grosshans , G. Van Assche , J. Wenger , R. Brouri , N. J. Cerf , Ph. Grangier

Privacy amplification (PA) is an indispensable component in classical and quantum cryptography. Error correction (EC) and data compression (DC) algorithms are also indispensable in classical and quantum information theory. We here study…

Quantum Physics · Physics 2022-02-01 Toyohiro Tsurumaru

A real-time Quantum Key Distribution System is developed in this paper. In the system, based on the feature of Field Programmable Gate Array (FPGA), secure key extraction control and algorithm have been optimally designed to perform…

Secure multi-party computation-based machine learning, referred to as MPL, has become an important technology to utilize data from multiple parties with privacy preservation. While MPL provides rigorous security guarantees for the…

Cryptography and Security · Computer Science 2022-08-19 Wenqiang Ruan , Mingxin Xu , Wenjing Fang , Li Wang , Lei Wang , Weili Han

Quantum computing revolutionizes the way of solving complex problems and handling vast datasets, which shows great potential to accelerate the machine learning process. However, data leakage in quantum machine learning (QML) may present…

Quantum Physics · Physics 2024-03-08 Keyi Ju , Xiaoqi Qin , Hui Zhong , Xinyue Zhang , Miao Pan , Baoling Liu

We give a fast algorithm to optimally compose privacy guarantees of differentially private (DP) algorithms to arbitrary accuracy. Our method is based on the notion of privacy loss random variables to quantify the privacy loss of DP…

Data Structures and Algorithms · Computer Science 2021-10-27 Sivakanth Gopi , Yin Tat Lee , Lukas Wutschitz

We report the first quantum key distribution (QKD) systems capable of delivering sustainable, real-time secure keys continuously at rates exceeding 10 Mb/s. To achieve such rates, we developed high speed post-processing modules, achieving…

In this brief, we present an enhanced privacy-preserving distributed estimation algorithm, referred to as the ``Double-Private Algorithm," which combines the principles of both differential privacy (DP) and cryptography. The proposed…

Signal Processing · Electrical Eng. & Systems 2024-03-19 Mehdi Korki , Fatemehsadat Hosseiniamin , Hadi Zayyani , Mehdi Bekrani

Privacy-preserving data mining has become an important topic. People have built several multi-party-computation (MPC)-based frameworks to provide theoretically guaranteed privacy, the poor performance of real-world algorithms have always…

Cryptography and Security · Computer Science 2021-05-18 Xiaoyu Fan , Guosai Wang , Kun Chen , Xu He , Wei Xu

We propose and experimentally demonstrate a new scheme for measuring high-dimensional phase states using a two-photon interference technique, which we refer to as quantum-controlled measurement. Using this scheme, we implement a…

Discrete-modulation continuous-variable quantum key distribution has the potential for large-scale deployment in the secure quantum communication networks due to low implementation complexity and compatibility with the current telecom…

Quantum Physics · Physics 2023-12-14 Pu Wang , Jianqiang Liu , Zhenguo Lu , Xuyang Wang , Yongmin Li

In many real-world scenarios, multiple data providers need to collaboratively perform analysis of their private data. The challenges of these applications, especially at the big data scale, are time and resource efficiency as well as…

Databases · Computer Science 2024-06-18 Ala Eddine Laouir , Abdessamad Imine

The performance of quantum key distribution (QKD) is severely limited by multi-photon pulses emitted by laser sources due to the photon-number splitting attack. Coherent-one-way (COW) QKD has been introduced as a promising solution to…

Quantum Physics · Physics 2021-01-06 Javier González-Payo , Róbert Trényi , Weilong Wang , Marcos Curty

We present a simple method to obtain an upper bound on the achievable secret key rate in quantum key distribution (QKD) protocols that use only unidirectional classical communication during the public-discussion phase. This method is based…

Quantum Physics · Physics 2009-11-13 Tobias Moroder , Marcos Curty , Norbert Lütkenhaus

Decoy-state quantum key distribution (QKD) is undoubtedly the most efficient solution to handle multi-photon signals emitted by laser sources, and provides the same secret key rate scaling as ideal single-photon sources. It requires,…

Quantum Physics · Physics 2023-12-22 Xoel Sixto , Guillermo Currás-Lorenzo , Kiyoshi Tamaki , Marcos Curty

The shuffle model of differential privacy provides promising privacy-utility balances in decentralized, privacy-preserving data analysis. However, the current analyses of privacy amplification via shuffling lack both tightness and…

Cryptography and Security · Computer Science 2024-07-30 Shaowei Wang , Yun Peng , Jin Li , Zikai Wen , Zhipeng Li , Shiyu Yu , Di Wang , Wei Yang

Using quantum key distribution (QKD) protocols, a secret key is created between two distant users (transmitter and receiver) at a particular key rate. Quantum technology can facilitate secure communication for cryptographic applications,…

Quantum Physics · Physics 2026-01-09 Venkat Abhignan , Mohit Mittal , Aditi Das , Megha Shrivastava

We study a protocol for distributed computation called shuffled check-in, which achieves strong privacy guarantees without requiring any further trust assumptions beyond a trusted shuffler. Unlike most existing work, shuffled check-in…

Machine Learning · Computer Science 2023-07-06 Seng Pei Liew , Satoshi Hasegawa , Tsubasa Takahashi