Results 31 to 40 of about 47,575 (276)
Publishing Microdata with a Robust Privacy Guarantee [PDF]
, 2012 Today, the publication of microdata poses a privacy threat. Vast research has striven to define the privacy condition that microdata should satisfy before it is released, and devise algorithms to anonymize the data so as to achieve this condition.
Cao, Jianneng, Karras, Panagiotis
core +2 more sources
Quantification of De-anonymization Risks in Social Networks
, 2017 The risks of publishing privacy-sensitive data have received considerable attention recently. Several de-anonymization attacks have been proposed to re-identify individuals even if data anonymization techniques were applied.
Ji, Shouling +4 more
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Algorithms to anonymize structured medical and healthcare data: A systematic review
Frontiers in Bioinformatics, 2022 Introduction: With many anonymization algorithms developed for structured medical health data (SMHD) in the last decade, our systematic review provides a comprehensive bird’s eye view of algorithms for SMHD anonymization.Methods: This systematic review ...
Ali Sepas +6 more
doaj +1 more source
Energy efficient privacy preserved data gathering in wireless sensor networks having multiple sinks [PDF]
, 2009 Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-tomany structures are evolved due to need for conveying collected event information to ...
Bahsi, Hayretdin +2 more
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Utility-preserving anonymization for health data publishing
BMC Medical Informatics and Decision Making, 2017 Background Publishing raw electronic health records (EHRs) may be considered as a breach of the privacy of individuals because they usually contain sensitive information.
Hyukki Lee +3 more
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IEEE AccessData anonymization is an essential prerequisite that enables data sharing in a privacy-preserving manner. However, anonymization affects the quality of the data and thus might affect the performance of later conducted data analysis.
Roland Stenger +4 more
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Improving MapReduce privacy by implementing multi-dimensional sensitivity-based anonymization
Journal of Big Data, 2017 Big data is predominantly associated with data retrieval, storage, and analytics. Data analytics is prone to privacy violations and data disclosures, which can be partly attributed to the multi-user characteristics of big data environments.
Mohammed Al-Zobbi +2 more
doaj +1 more source
Assessing Data Usefulness for Failure Analysis in Anonymized System Logs
, 2018 System logs are a valuable source of information for the analysis and understanding of systems behavior for the purpose of improving their performance. Such logs contain various types of information, including sensitive information.
Ciorba, Florina M., Ghiasvand, Siavash
core +1 more source
Anonymizing Temporal Data [PDF]
2010 IEEE International Conference on Data Mining, 2010 Temporal data are time-critical in that the snapshot at each timestamp must be made available to researchers in a timely fashion. However, due to the limited data, each snapshot likely has a skewed distribution on sensitive values, which renders classical anonymization methods not possible.
Ke Wang +3 more
openaire +1 more source
Utility-driven assessment of anonymized data via clustering
Scientific Data, 2022 In this study, clustering is conceived as an auxiliary tool to identify groups of special interest. This approach was applied to a real dataset concerning an entire Portuguese cohort of higher education Law students.
Maria Eugénia Ferrão +2 more
doaj +1 more source