Results 11 to 20 of about 51,151 (259)
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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MultiRelational k-Anonymity [PDF]
2007 IEEE 23rd International Conference on Data Engineering, 2007 k-anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. Much research has been done to modify a single table dataset to satisfy anonymity constraints.
Nergiz, M.E., Clifton, C., Nergiz, A.E.
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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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top-k Path Greedy Generalization Algorithm of Anonymity Shortest Path [PDF]
Jisuanji gongcheng, 2016 With the development of social networks,the issues of privacy preservation arouse extensive attention.It can cause privacy disclosure of the shortest path if weighted social network data are protected before its publication.In order to solve this issue ...
CHEN Weihe,DING Leilei
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Computers & Security, 2014 Abstract Anonymization-based privacy protection ensures that published data cannot be linked back to an individual. The most common approach in this domain is to apply generalizations on the private data in order to maintain a privacy standard such as k -anonymity.
Nergiz, Mehmet Ercan +1 more
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Spatiotemporal Mobility Based Trajectory Privacy-Preserving Algorithm in Location-Based Services
Sensors, 2021 Recent years have seen the wide application of Location-Based Services (LBSs) in our daily life. Although users can enjoy many conveniences from the LBSs, they may lose their trajectory privacy when their location data are collected.
Zhiping Xu +4 more
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