Results 11 to 20 of about 7,115,390 (197)
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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Implementasi Algoritma Mondrian Multidimensional K-Anonymity pada Biodata Calon Legislatif
Jurnal Eksplora Informatika, 2021 Uni Eropa menerbitkan sebuah peraturan yang bernama General Data Protection Regulation (GDPR) untuk menjaga privasi warga. Peraturan ini meregulasi penyebaran data-data pribadi seperti nama, nomor telepon atau alamat yang mungkin akan digunakan untuk ...
Adam Akbar +2 more
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Recommendation with k-anonymized Ratings [PDF]
CoRR, 2017 Recommender systems are widely used to predict personalized preferences of goods or services using users' past activities, such as item ratings or purchase histories. If collections of such personal activities were made publicly available, they could be used to personalize a diverse range of services, including targeted advertisement or recommendations.
Jun Sakuma, Tatsuya Osame
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Privacy-preserving data compression scheme for k-anonymity model based on Huffman coding
网络与信息安全学报, 2023 The k-anonymity model is widely used as a data anonymization technique for privacy protection during the data release phase.However, with the advent of the big data era, the generation of vast amounts of data poses challenges to data storage.However, it ...
Yue YU, Xianzheng LIN, Weihai LI, Nenghai YU
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Privacy Protection Method for k Degree Anonymity Based on Node Classification [PDF]
Jisuanji gongcheng, 2020 Existing k degree anonymous privacy protection methods usually damage the graph structure significantly and cannot resist structural background knowledge attacks.To address the problem,this paper proposes an improved k degree anonymous privacy protection
JIN Ye, DING Xiaobo, GONG Guoqiang, Lü Ke
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Privacy Protection Method in Continuous Publishing of Graph Data [PDF]
Jisuanji gongcheng, 2022 With the development of Internet technology and popularity of intelligent terminals, a large amount of user privacy data have been generated in social networks.The public release of social network data increases the risk of user privacy disclosure ...
ZHU Liming, DING Xiaobo, GONG Guoqiang
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, 2005 It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in order to ensure a required statistical significance, represent a large number of individuals and thus conceal individual identities: this is the case of the minimum support ...
ATZORI, MAURIZIO +3 more
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On the $$(k,\ell )$$ ( k , ℓ ) -anonymity of networks via their k-metric antidimension
Scientific Reports, 2023 This work focuses on the $$(k,\ell )$$ ( k , ℓ ) -anonymity of some networks as a measure of their privacy against active attacks. Two different types of networks are considered.
Elena Fernández +3 more
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Achieving P-Sensitive K-Anonymity via Anatomy [PDF]
, 2009 Privacy-preserving data publishing is to protect sensitive information of individuals in published data while the distortion ratio of the data is minimized. One well-studied approach is the K-anonymity model.
Xiaoxun Sun +10 more
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