منابع مشابه
Protecting Privacy Using k-Anonymity
Objective: There is increasing pressure to share health information and even make it publicly availab 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 kanonymity. There have been no evaluations of the actual re-identification probabili...
متن کاملk-Anonymity: A Model for Protecting Privacy
Consider a data holder, such as a hospital or a bank, that has a privately held collection of person-specific, field structured data. Suppose the data holder wants to share a version of the data with researchers. How can a data holder release a version of its private data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data rema...
متن کاملProtecting Privacy by Multi-dimensional K-anonymity
Privacy protection for incremental data has a great effect on data availability and practicality. Kanonymity is an important approach to protect data privacy in data publishing scenario. However, it is a NP-hard problem for optimal k-anonymity on dataset with multiple attributes. Most partitions in k-anonymity at present are single-dimensional. Now research on k-anonymity mainly focuses on gett...
متن کاملA Customizable k-Anonymity Model for Protecting Location Privacy
Continued advances in mobile networks and positioning technologies have created a strong market push for location-based services (LBSs). Examples include location-aware emergency services, location based service advertisement, and location sensitive billing. One of the big challenges in wide deployment of LBS systems is the privacy-preserving management of location-based data. Without safeguard...
متن کاملMulti-dimensional k-anonymity Based on Mapping for Protecting Privacy
Data release has privacy disclosure risk if not taking any protection policy. Although attributes that clearly identify individuals, such as Name, Identity Number, are generally removed or decrypted, attackers can still link these databases with other released database on attributes (Quasi-identifiers) to re-identify individual’s private information. K-anonymity is a significant method for priv...
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ژورنال
عنوان ژورنال: Journal of the American Medical Informatics Association
سال: 2008
ISSN: 1527-974X,1067-5027
DOI: 10.1197/jamia.m2716