A secure distributed framework for achieving k-anonymity
K-Anonymity: A Big Player in Location Privacy for Mobile IV. W HAT IS K-ANONYMITY Anonymity can be defined as “a state of being not identifiable within a set of subjects, the anonymity set” [6]. The concept of k-anonymity was originally introduced in the context of relational data privacy research. It pointed out the question of “How can a data holder release a version of its private data with k-anonymity - Data Privacy Lab k-anonymity: a model for protecting privacy Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression . Also appears as Protecting respondents identities in microdata release, IEEE Transactions on Knowledge and Data Engineering , 2001.
The evolution of the Internet of Things is significantly affected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR). The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed and unambiguous consent to collect and process
l-Diversity: Privacy Beyond k-Anonymity | Request PDF To further improve privacy properties of the k-anonymity mechanism, the l-diversity concept has been introduced (Machanavajjhala et al., 2006): the cloaked region containing the k individuals must k-anonymity and SQL Server – Information with Insight Jan 09, 2017
l-Diversity: Privacy Beyond k-Anonymity | Request PDF
A Privacy-Preserving Trajectory Publication Method Based Since the generation of k-anonymity technology originates from the privacy protection problem of relational databases, the quasi-identifiers and sensitive attributes in the database are easy to define. But when k-anonymity is applied to the high-dimensional data field of trajectory, these attributes become difficult to define . Constrained k-Anonymity: Privacy with Generalization Abstract: In the last few years, due to new privacy regulations, research in data privacy has flourished. A large number of privacy models were developed most of which are based on the k-anonymity property. Because of several shortcomings of the k-anonymity model, other privacy models were introduced (l-diversity, p-sensitive k-anonymity, ( α, k) – anonymity, CERIAS Tech Report 2005-134 Privacy-Preserving Distributed