Privacy

By Jin H. Im. 2002

1,308 citations recorded by the source corpus.

Subfields: Public Health, Environmental and Occupational Health

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Public Health, Environmental and Occupational Health

1. Vitaly Feldman
2. Isabel Wagner
3. Alejandro E. Brito
4. Shantanu D. Rane
5. Kobbi Nissim
6. Alessandro Acquisti
7. Moni Naor
8. M. Franklin

Citations in the corpus

• Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers (2013, background): “Differential privacy [19, 14, 9] protects against unintentional disclosure of potentially sensitive information related to a single record of a database D .”
• Concentrated Differential Privacy (2016, background): “Differential privacy is a mathematically rigorous definition of privacy tailored to analysis of large datasets and equipped with a formal measure of privacy loss [DMNS06, Dwo06].”
• On the Difficulties of Disclosure Prevention in Statistical Databases or The Case for Differential Privacy (2010, background): “See also [30, 28, 5, 4, 30, 3, 27] for other works dealing with the notion.”
• Distributed Private Data Analysis: On Simultaneously Solving How and What (2008, methodology): “We examine the combination of two directions in the field of privacy concerning distributed private inputs – secure function evaluation [26, 18, 4, 1] and differential privacy [11, 8].”
• Universally utility-maximizing privacy mechanisms (2008, background): “Many of the mechanisms studied in the literature are oblivious [3, 5, 12, 9], though there are notable exceptions [19, 21].”
• Differentially private combinatorial optimization (2009, background): “Differential privacy is a relatively recent privacy definition (e.g., see [DMNS06, Dwo06, NRS07, BLR08, KLN + 08, FFKN09, DNR + 09], and see [Dwo08] for an excellent survey), that tries to capture the intuition of individual privacy.”
• Private stochastic convex optimization: optimal rates in linear time (2020, background): “The notion of differential privacy is by now a de facto standard for statistical data privacy [DMNS06, Dwo06, DR14]. for all datasets S and S (cid:48) that differ in a single data element and for all events O in the output space of A , we have Starting with Concentrated Differential Privacy [DR16],…”
• Context-Aware Generative Adversarial Privacy (2017, background): “One of the most popular context-free notions of privacy is differential privacy (DP) [19, 20, 21].”
• The relationship between trust in AI and trustworthy machine learning technologies (2019, background): “Careless preparation of the stored data would leak information to an attacker [61] but confidentiality can be enhanced in many ways, for instance through approaches for differential privacy [1, 34], homomorphic encryption [47] or cryptography integrated in machine learning algorithms [79].”
• Technical Privacy Metrics (2015, background): “Approximate differential privacy relaxes differential privacy by allowing an additional small additive constant δ [Dwork et al. 2006].”
• Identifying Opportunities for Valuable Encounters: Toward Context-Aware Social Matching Systems (2015, background): “Privacy is a multifaceted and com­plex topic with numerous varying de.nitions, the simplest being control over knowl­edge about oneself [Fried 1968].”
• Indiscriminate mass surveillance and the public sphere (2016, neutral): “…it is sometimes argued that privacy not protects individual freedom of action but that it also safe-guards certain forms of social interaction (Fried 1968; Rachels 1975; Schoeman 1984; Solove 2007) Therefore, many authors hold that privacy is both valuable for the individual and for society…”
• Factors influencing acceptance of technology for aging in place: A systematic review (2014, background): “, 2011 [38] × × × × – Qualitative Focus groups 65 USA van Hoof et al.”
• Is privacy privacy? (2018, background): “seclusion or solitude, or into his or her private affairs; public disclosure of embarrassing private facts about an individual; publicity placing one in a false light in the public eye; and appropriation of one’s likeness for the advantage of another [13].”
• Nonlinear Discrete Optimization (2010, background): “Let us mention the papers [8], [22], and [36], and the references therein, as informative sources corresponding to these three lines of investigation.”
• Understanding Privacy Online: Development of a Social Contract Approach to Privacy (2016, background): “51), in order to have relationships (Fried 1968), and to converse and trade information (Singleton 1998) pervades justifications for privacy norms.”