Results 21 to 30 of about 51,151 (259)
p-probabilistic k-anonymous microaggregation for the anonymization of surveys with uncertain participation [PDF]
, 2016 We develop a probabilistic variant of k-anonymous microaggregation which we term p-probabilistic resorting to a statistical model of respondent participation in order to aggregate quasi-identifiers in such a manner that k-anonymity is concordantly ...
Forné Muñoz, Jorge +3 more
core +2 more sources
Location Anonymization With Considering Errors and Existence Probability [PDF]
, 2017 Mobile devices that can sense their location using GPS or Wi-Fi have become extremely popular. However, many users hesitate to provide their accurate location information to unreliable third parties if it means that their identities or sensitive ...
Akihiko Ohsuga, Yuichi Sei
core +2 more sources
The K-Anonymization Method Satisfying Personalized Privacy Preservation
Chemical Engineering Transactions, 2015 Even if k-anonymity model can prevent publishing data from disclosing privacy effectively and efficiently, due to the uneven distribution of the sensitive data, ordinary k-anonymization method cannot guarantee each tuple satisfying the personalized ...
J.L. Song +4 more
doaj +1 more source
(α, k)-anonymous data publishing [PDF]
Journal of Intelligent Information Systems, 2009 Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information.
Raymond Wong +3 more
openaire +2 more sources
PTA: An Efficient System for Transaction Database Anonymization
IEEE Access, 2016 Several approaches have been proposed to anonymize relational databases using the criterion of k-anonymity, to avoid the disclosure of sensitive information by re-identification attacks.
Jerry Chun-Wei Lin +3 more
doaj +1 more source
Attribute Couplet Attacks and Privacy Preservation in Social Networks
IEEE Access, 2017 The emerging of social networks, e.g., Facebook, Twitter, and Instagram, has eventually changed the way in which we live. Social networks are acquiring and storing a significant amount of profile information and daily activities of over billions of ...
Dan Yin, Yiran Shen, Chenyang Liu
doaj +1 more source
Preserving prosumer privacy in a district level smart grid [PDF]
, 2016 This study presents the anonymization of consumer data in a district-level smart grid using the k-anonymity approach. The data utilized in this study covers the demographic information and associated energy consumption of consumers.
Mourshed, Monjur +3 more
core +2 more sources
MI Loss Evaluation Model for k-Anonymity in PPDM [PDF]
Jisuanji gongcheng, 2022 Privacy Preserving Data Mining(PPDM) uses methods such as anonymization to allow data owners to safely publish data sets that are effectively available in data mining without revealing private information.The k-anonymity algorithm, one of the most widely
GU Qingzhu, DONG Hongbin
doaj +1 more source
Entropy, 2023 Data anonymization is a technique that safeguards individuals’ privacy by modifying attribute values in published data. However, increased modifications enhance privacy but diminish the utility of published data, necessitating a balance between privacy ...
Reza Ahmadi Khatir +2 more
doaj +1 more source
Towards trajectory anonymization: a generalization-based approach [PDF]
, 2009 Trajectory datasets are becoming popular due to the massive usage of GPS and locationbased services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets.
Atzori, Maurizio +5 more
core +2 more sources