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The Ontological Interpretation of Informational Privacy [PDF]

open access: greenEthics and Information Technology, 2005
The paper outlines a new interpretation of informational privacy and of its moral value. The main theses defended are: (a) informational privacy is a function of the ontological friction in the infosphere, that is, of the forces that oppose the information flow within the space of information; (b) digital ICTs (information and communication ...
Luciano Floridi
openalex   +5 more sources

Privacy and Health Information Technology [PDF]

open access: green, 2009
The increased use of health information technology (health IT) is a common element of nearly every health reform proposal because it has the potential to decrease costs, improve health outcomes, coordinate care, and improve public health.
Deven McGraw
openalex   +4 more sources

An information-theoretic approach to privacy [PDF]

open access: green2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2010
Ensuring the usefulness of electronic data sources while providing necessary privacy guarantees is an important unsolved problem. This problem drives the need for an overarching analytical framework that can quantify the safety of personally identifiable information (privacy) while still providing a quantifable benefit (utility) to multiple legitimate ...
Lalitha Sankar   +2 more
openalex   +4 more sources

How Perceptions of Information Privacy and Security Impact Consumer Trust in Crypto-Payment: An Empirical Study

open access: yesIEEE Access, 2022
The ever-increasing acceptance of cryptocurrencies has fueled applications beyond investment purposes. Crypto-payment is one such application that can bring radical changes to financial transactions in many industries, particularly e-commerce and online ...
Atefeh Mashatan   +2 more
semanticscholar   +1 more source

Information Design for Differential Privacy [PDF]

open access: yesProceedings of the 23rd ACM Conference on Economics and Computation, 2021
Firms and statistical agencies must protect the privacy of the individuals whose data they collect, analyze, and publish. Increasingly, these organizations do so by using publication mechanisms that satisfy differential privacy. We consider the problem of choosing such a mechanism so as to maximize the value of its output to end users.
Nathan Yoder, Ian M. Schmutte
openaire   +3 more sources

Validity and Reliability of the Scale Internet Users’ Information Privacy Concerns (IUIPC)

open access: yesProceedings on Privacy Enhancing Technologies, 2021
Internet Users’ Information Privacy Concerns (IUIPC-10) is one of the most endorsed privacy concern scales. It is widely used in the evaluation of human factors of PETs and the investigation of the privacy paradox. Even though its predecessor Concern For
Thomas Gross
semanticscholar   +1 more source

Joint Protection of Energy Security and Information Privacy for Energy Harvesting: An Incentive Federated Learning Approach

open access: yesIEEE Transactions on Industrial Informatics, 2021
Energy harvesting (EH) is a promising and critical technology to mitigate the dilemma between the limited battery capacity and the increasing energy consumption in the Internet of everything. However, the current EH system suffers from energy-information
Qianqian Pan   +5 more
semanticscholar   +1 more source

Checking Only When It Is Necessary: Enabling Integrity Auditing Based on the Keyword With Sensitive Information Privacy for Encrypted Cloud Data

open access: yesIEEE Transactions on Dependable and Secure Computing, 2021
The public cloud data integrity auditing technique is used to check the integrity of cloud data through the Third Party Auditor (TPA). In order to make it more practical, we propose a new paradigm called integrity auditing based on the keyword with ...
Xiang Gao   +4 more
semanticscholar   +1 more source

Context-Aware Local Information Privacy

open access: yesIEEE Transactions on Information Forensics and Security, 2021
In this paper, we study Local Information Privacy (LIP). As a context-aware privacy notion, LIP relaxes the de facto standard privacy notion of local differential privacy (LDP) by incorporating prior knowledge and therefore achieving better utility.
Bo Jiang   +3 more
semanticscholar   +1 more source

Deep Learning with Differential Privacy [PDF]

open access: yesConference on Computer and Communications Security, 2016
Machine learning techniques based on neural networks are achieving remarkable results in a wide variety of domains. Often, the training of models requires large, representative datasets, which may be crowdsourced and contain sensitive information.
Martín Abadi   +6 more
semanticscholar   +1 more source

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