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Investigation and Application of Differential Privacy in Bitcoin
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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Rényi Differential Privacy [PDF]
We propose a natural relaxation of differential privacy based on the Renyi divergence. Closely related notions have appeared in several recent papers that analyzed composition of differentially private mechanisms. We argue that the useful analytical tool can be used as a privacy definition, compactly and accurately representing guarantees on the tails ...
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Randomized Privacy Budget Differential Privacy
arXiv admin note: text overlap with arXiv:2009 ...
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Differential Privacy: A Primer for a Non-Technical Audience
Differential privacy is a formal mathematical framework for quantifying and managing privacy risks. It provides provable privacy protection against a wide range of potential attacks, including those currently unforeseen. Differential privacy is primarily
Honaker, James +9 more
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Per-instance Differential Privacy
We consider a refinement of differential privacy --- per instance differential privacy (pDP), which captures the privacy of a specific individual with respect to a fixed data set.
Yu-Xiang Wang
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LinkedIn's Audience Engagements API
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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To appear in the 2022 IEEE International Symposium on Information ...
Ziqi Zhou 0005 +5 more
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Many data applications have certain invariant constraints due to practical needs. Data curators who employ differential privacy need to respect such constraints on the sanitized data product as a primary utility requirement. Invariants challenge the formulation, implementation, and interpretation of privacy guarantees.
Jie Gao 0001, Ruobin Gong, Fang-Yi Yu
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Privacy-Preserving Bin-Packing With Differential Privacy
With the emerging of e-commerce, package theft is at a high level: It is reported that 1.7 million packages are stolen or lost every day in the U.S. in 2020, which costs $25 million every day for the lost packages and the service.
Tianyu Li +2 more
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