Results 31 to 40 of about 1,504,715 (296)

Information Privacy Assimilation

open access: yesInternational Journal of Digital Strategy, Governance, and Business Transformation, 2022
This paper proposes a framework to understand organizations' perspectives while safeguarding customers' information privacy. Following a detailed literature review, a broad conceptual model was developed to build a theory based on a multi-site, multi-case study approach.
Suhasish Halder   +2 more
openaire   +1 more source

Gamification vs. Privacy: Identifying and Analysing the Major Concerns

open access: yesFuture Internet, 2019
Gamification, the use of game design elements in applications that are not games, has been developed to provide attractive environments and maintain user interest in several domains.
Aikaterini-Georgia Mavroeidi   +3 more
doaj   +1 more source

Lightweight Conversion from Arithmetic to Boolean Masking for Embedded IoT Processor

open access: yesApplied Sciences, 2019
A masking method is a widely known countermeasure against side-channel attacks. To apply a masking method to cryptosystems consisting of Boolean and arithmetic operations, such as ARX (Addition, Rotation, XOR) block ciphers, a masking conversion ...
HanBit Kim, Seokhie Hong, HeeSeok Kim
doaj   +1 more source

Information Extraction Under Privacy Constraints

open access: yes, 2016
A privacy-constrained information extraction problem is considered where for a pair of correlated discrete random variables $(X,Y)$ governed by a given joint distribution, an agent observes $Y$ and wants to convey to a potentially public user as much ...
Alajaji, Fady   +3 more
core   +2 more sources

On-line privacy behavior: using user interfaces for salient factors [PDF]

open access: yes, 2014
The problem of privacy in social networks is well documented within literature; users have privacy concerns however, they consistently disclose their sensitive information and leave it open to unintended third parties.
Hughes-Roberts, T, Kani-Zabihi, E
core   +2 more sources

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

open access: yes, 2019
In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy ...
A Wasef   +8 more
core   +3 more sources

Ensuring Privacy with Constrained Additive Noise by Minimizing Fisher Information [PDF]

open access: yes, 2018
The problem of preserving the privacy of individual entries of a database when responding to linear or nonlinear queries with constrained additive noise is considered.
Farokhi, Farhad, Sandberg, Henrik
core   +2 more sources

Personal Information Privacy Settings of Online Social Networks and their Suitability for Mobile Internet Devices

open access: yes, 2013
Protecting personal information privacy has become a controversial issue among online social network providers and users. Most social network providers have developed several techniques to decrease threats and risks to the users privacy.
Aldhafferi, Nahier   +2 more
core   +1 more source

Citizens’ Information Privacy Protection Model in e-Government for Developing Countries [PDF]

open access: yesپژوهش‌های مدیریت عمومی, 2016
The most important aim of this study is to propose a model for protecting citizens’ information privacy in e-Government for developing countries. This study develops theoretical foundations and models of e-Government in  judicial-legal dimension.
Mohammad Taghi Taghavifard   +3 more
doaj   +1 more source

On the relation between Differential Privacy and Quantitative Information Flow [PDF]

open access: yes, 2011
Differential privacy is a notion that has emerged in the community of statistical databases, as a response to the problem of protecting the privacy of the database's participants when performing statistical queries.
A. Ghosh   +13 more
core   +7 more sources

Home - About - Disclaimer - Privacy