Results 1 to 10 of about 51,151 (259)
Daily activity locations k-anonymity for the evaluation of disclosure risk of individual GPS datasets [PDF]
International Journal of Health Geographics, 2020 Background Personal privacy is a significant concern in the era of big data. In the field of health geography, personal health data are collected with geographic location information which may increase disclosure risk and threaten personal geoprivacy ...
Jue Wang, Mei-Po Kwan
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A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks. [PDF]
PLoS ONE, 2017 Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications.
Haitao Zhang +4 more
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Pattern-Guided k-Anonymity [PDF]
Algorithms, 2013 We suggest a user-oriented approach to combinatorial data anonymization. A data matrix is called k-anonymous if every row appears at least k times—the goal of the NP-hard k-ANONYMITY problem then is to make a given matrix k-anonymous by suppressing ...
Rolf Niedermeier +2 more
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Protecting privacy using k-anonymity. [PDF]
J Am Med Inform Assoc, 2008 AbstractObjective: There is increasing pressure to share health information and even make it publicly available. However, such disclosures of personal health information raise serious privacy concerns. To alleviate such concerns, it is possible to anonymize the data before disclosure. One popular anonymization approach is k-anonymity.
El Emam K, Dankar FK.
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Nonexposure Accurate Location K-Anonymity Algorithm in LBS [PDF]
The Scientific World Journal, 2014 This paper tackles location privacy protection in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services.
Jinying Jia, Fengli Zhang
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k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification [PDF]
Entropy, 2018 Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such
Blaž Meden +3 more
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Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset. [PDF]
PLoS ONE, 2016 Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users' privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries ...
Haitao Zhang +4 more
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网络与信息安全学报, 2023 The use of location-based service brings convenience to people’s daily lives, but it also raises concerns about users’ location privacy.In the k-nearest neighbor query problem, constructing K-anonymizing spatial regions is a method used to protects users’
Saite CHEN, Weihai LI, Yuanzhi YAO, Nenghai YU
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KAB: A new k-anonymity approach based on black hole algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 K-anonymity is the most widely used approach to privacy preserving microdata which is mainly based on generalization. Although generalization-based k-anonymity approaches can achieve the privacy protection objective, they suffer from information loss ...
Lynda Kacha +2 more
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Semantic-based Privacy-preserving Record Linkage.
International Journal of Population Data Science, 2022 Introduction Sharing aggregated electronic health records (EHRs) for integrated health care and public health studies is increasingly demanded. Patient privacy demands that anonymisation procedures are in place for data sharing.
Yang Lu
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