An Improved Algorithm of Individuation K-Anonymity for Multiple Sensitive Attributes
Sign Up to like & getrecommendations! Published in 2017 at "Wireless Personal Communications"
DOI: 10.1007/s11277-016-3922-4
Abstract: AbstractAt present, most of privacy preserving approaches in data publishing are applied to single sensitive attribute. However, applying single-sensitive-attribute privacy preserving techniques directly into data with multiple sensitive attributes often causes leakage of large amount… read more here.
Keywords: sensitive attributes; multiple sensitive; algorithm individuation; individuation anonymity ... See more keywords
An enhanced dynamic KC-slice model for privacy preserving data publishing with multiple sensitive attributes by inducing sensitivity
Sign Up to like & getrecommendations! Published in 2018 at "Journal of King Saud University - Computer and Information Sciences"
DOI: 10.1016/j.jksuci.2018.09.013
Abstract: Abstract Privacy Preserving Data Publishing (PPDP) is an important aspect of real world scenarios. PPDP moves the researcher in the right direction by maintaining privacy and utility trade-off while publishing the data. This paper presents… read more here.
Keywords: sensitive attributes; multiple sensitive; privacy; slice model ... See more keywords
Identifying Reliability-Critical Primary Inputs of Combinational Circuits Based on the Model of Gate-Sensitive Attributes
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2022.3142194
Abstract: The identification of reliability-critical primary input leads (RCPIs) plays an important role in the testing and prediction of reliability boundaries of logic circuits. This article presents a gate-sensitive-attributes-based approach to estimate the criticality of the… read more here.
Keywords: gate sensitive; sensitive attributes; primary; reliability ... See more keywords
Anonymization of Sensitive Quasi-Identifiers for l-Diversity and t-Closeness
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2017.2698472
Abstract: A number of studies on privacy-preserving data mining have been proposed. Most of them assume that they can separate quasi-identifiers (QIDs) from sensitive attributes. For instance, they assume that address, job, and age are QIDs… read more here.
Keywords: quasi identifiers; diversity closeness; anonymization; sensitive attributes ... See more keywords
Protecting Sensitive Attributes by Adversarial Training Through Class-Overlapping Techniques
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2023.3236180
Abstract: In recent years, machine learning as a service (MLaaS) has brought considerable convenience to our daily lives. However, these services raise the issue of leaking users’ sensitive attributes, such as race, when provided through the… read more here.
Keywords: attributes adversarial; sensitive attributes; class overlapping; class ... See more keywords
Privacy Preserving Data Publishing for Heterogeneous Multiple Sensitive Attributes with Personalized Privacy and Enhanced Utility
Sign Up to like & getrecommendations! Published in 2020 at "Systematic Reviews in Pharmacy"
DOI: 10.31838/srp.2020.9.151
Abstract: In recent years, personal data availability has become vast, which leads to the concept of Privacy-preserving. Privacy-Preserving is an essential issue in all research fields. Many privacy methods are available for privacy-preserving data publishing (PPDP);… read more here.
Keywords: sensitive attributes; privacy preserving; data publishing; preserving data ... See more keywords