Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression

By Pierangela Samarati, Latanya Sweeney. 1998

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Citations in the corpus

Marginal Release Under Local Differential Privacy (2017, background): “A(D) = x] Pr[A(D0) = x] exp(); (1) where xis any permitted output. The model has risen in popularity and adoption compared to earlier attempts to codify privacy (such as k-anonymity and ‘-diversity [32, 24]), which can leak sensitive information. It has been a topic of inquiry for diverse research c”
Differentially Private Password Frequency Lists (2016, background): “In response to de-anonymization attacks researchers began to propose formal data privacy models like k-anonymity [35], [32] and `-diversity [25].”
Data Synthesis based on Generative Adversarial Networks (2018, background): “One of the most fundamental and widely adopted privacy models is k-anonymity introduced by Samarati and Sweeney [32].”
A Privacy-Preserving Index for Range Queries (2004, background): “Another important privacy-measure, that of k-anonymity [14] has been introduced earlier in section 6.”
AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020, unknown): “To accomplish the anonymization of medical imaging data, approaches such as k-anonymity [55], [56], l-diversity [57] and t-closeness [58] are typically used.”
Knowledge Graphs (2020, unknown): “A first approach to anonymisation is to suppress and generalise knowledge in a graph such that individuals cannot be identified, based on k-anonymity [458]32, l-diversity [315]33, etc.”
Privacy and Data Protection by Design - from policy to engineering (2014, background): “We have mentioned above -differential privacy [93] and k-anonymity [177].”
Edge Analytics in the Internet of Things (2015, background): “For example, the accuracy of location meta-data associated with a sequence of video frames may be lowered to meet the needs of k-anonymity in location privacy [11].”
K-isomorphism: privacy preserving network publication against structural attacks (2010, background): “Recently, several methods [32, 19] have been proposed to achieve k-anonymity [23, 22, 24] based on various adversary knowledge.”
Virtual trip lines for distributed privacy-preserving traffic monitoring (2008, background): “The k-anonymity concept [53, 56] provides a guaranteed level of anonymity for a database, although some recent studies [46, 40] have identified weaknesses.”
Transforming data to satisfy privacy constraints (2002, methodology): “For this case we define a metric which captures some general notion of information loss as was done in the earlier works [15, 17, 14].”
Trustworthy AI: From Principles to Practices (2021, background): “Different principles of quantitative data anonymization have been developed, such as k-anonymity [288], (c,k )-safety [236], and δ -presence [253].”
Context-Aware Generative Adversarial Privacy (2017, methodology): “This is done by stripping oﬀ personally identiﬁable information (e.g., ﬁrst and last name, social security number, IDs, etc.) [41, 57, 65].”
Privacy: Theory meets Practice on the Map (2008, background): “These algorithms include generalizations [23], [24], [25], cell and tuple suppression [26], [25], random perturbation [22], [27], publishing marginals that satisfy a safety range [28], and data swapping [29] (where attributes”
A Survey of Inference Control Methods for Privacy-Preserving Data Mining (2008, methodology): “A different approach to facing the conflict between information loss and disclosure risk is suggested by Samarati and Sweeney [67, 66, 73, 74].”
Privacy-Preserving Data Mining: Models and Algorithms (2008, methodology): “These techniques include methods such as randomization [1], k-anonymity [16, 7], and l-diversity [11].”
An anonymous communication technique using dummies for location-based services (2005, background): “Gruteser and Grunwald proposed another mechanism called spatial and temporal cloaking [8] that conceals a user within a group of k people, called k-anonymous , which originated from k-anonymity [11].”