Results 11 to 20 of about 380,960 (294)
Privacy Profiles and Amplification by Subsampling
The Journal of Privacy and Confidentiality, 2020 Differential privacy provides a robust quantifiable methodology to measure and control the privacy leakage of data analysis algorithms. A fundamental insight is that by forcing algorithms to be randomized, their privacy leakage can be characterized by ...
Borja Balle +2 more
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Survey on Privacy Protection Solutions for Recommended Applications [PDF]
Jisuanji kexue, 2021 In the context of the era of big data,various industries want to train recommendation models based on user behavior data to provide users with accurate recommendations.The common characteristics of the used data are huge amount,carrying sensitive ...
DONG Xiao-mei, WANG Rui, ZOU Xin-kai
doaj +1 more source
State-Based Differential Privacy Verification and Enforcement for Probabilistic Automata
Mathematics, 2023 Roughly speaking, differential privacy is a privacy-preserving strategy that guarantees attackers to be unlikely to infer, from the previous system output, the dataset from which an output is derived. This work introduces differential privacy to discrete
Yuanxiu Teng, Zhiwu Li, Li Yin, Naiqi Wu
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Investigation and Application of Differential Privacy in Bitcoin
IEEE Access, 2022 Bitcoin is one of the best-known cryptocurrencies, which captivated researchers with its innovative blockchain structure. Examinations of this public blockchain resulted in many proposals for improvement in terms of anonymity and privacy.
Merve Can Kus, Albert Levi
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Bounded-Leakage Differential Privacy [PDF]
, 2020 We introduce and study a relaxation of differential privacy [Dwork et al., 2006] that accounts for mechanisms that leak some additional, bounded information about the database.
Ligett, Katrina +2 more
core +1 more source
Differential Privacy Made Easy [PDF]
, 2022 Data privacy is a major issue for many decades, several techniques have been developed to make sure individuals' privacy but still world has seen privacy failures. In 2006, Cynthia Dwork gave the idea of Differential Privacy which gave strong theoretical guarantees for data privacy.
arxiv +1 more source
New Program Abstractions for Privacy [PDF]
, 2020 Static program analysis, once seen primarily as a tool for optimising programs, is now increasingly important as a means to provide quality guarantees about programs. One measure of quality is the extent to which programs respect the privacy of user data.
C Dwork +5 more
core +1 more source
LinkedIn's Audience Engagements API
The Journal of Privacy and Confidentiality, 2021 We present a privacy system that leverages differential privacy to protect LinkedIn members' data while also providing audience engagement insights to enable marketing analytics related applications.
Ryan Rogers +7 more
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Privacy-Preserving Monotonicity of Differential Privacy Mechanisms
Applied Sciences, 2018 Differential privacy mechanisms can offer a trade-off between privacy and utility by using privacy metrics and utility metrics. The trade-off of differential privacy shows that one thing increases and another decreases in terms of privacy metrics and ...
Hai Liu +5 more
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Heterogeneous Differential Privacy
The Journal of Privacy and Confidentiality, 2017 The massive collection of personal data by personalization systems has rendered the preservation of privacy of individuals more and more difficult. Most of the proposed approaches to preserve privacy in personalization systems usually address this issue ...
Mohammad Alaggan +2 more
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