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K-anonymity model for privacy-preserving soccer fitness data publishing

Rong Li, Shushan An, Dong Li, Jian Dong, Wanjian Bai, Hongmei Li, Zhiming Zhang, Qingyang Lin, Nader Asnafi
2018 MATEC Web of Conferences  
At the same time, we apply the partitioning-based and k-means clustering-based two k-anonymity algorithms to the soccer fitness data publishing to trade-offs the data utility and the personal privacy.  ...  With the development of data mining technology, more and more researchers use the soccer fitness data to analyse the ranking of soccer athletes' and professional training.  ...  The reason for this is that as k increases, more and more records are generalized to have the same quasi-identifier value, resulting in greater loss of information.  ... 
doi:10.1051/matecconf/201818903007 fatcat:y5f4ld6serbmbpta3hf6fk3cmq

Protecting Privacy While Discovering and Maintaining Association Rules

Tran Khanh Dang, Josef Ku, Huynh V Q Phuong
2011 2011 4th IFIP International Conference on New Technologies, Mobility and Security  
Concretely, we use a k-anonymity model to preserve privacy while discovering and maintaining association rules through a novel algorithm, M3AR-member migration technique for maintaining association rules  ...  Instead, we propose a member migration technique that is more appropriate for the requirements of maintaining association rules.  ...  However, we do not use those techniques for some reasons: the attribute level generalization has the disadvantage of creating a lot of data distortion.  ... 
doi:10.1109/ntms.2011.5720635 dblp:conf/ntms/DangKQ11 fatcat:qks4zvbsl5ex3ek4pjpni27v34

Hiding the presence of individuals from shared databases

Mehmet Ercan Nergiz, Maurizio Atzori, Chris Clifton
2007 Proceedings of the 2007 ACM SIGMOD international conference on Management of data - SIGMOD '07  
We show that existing anonymization techniques are inappropriate for situations where δ-presence is a good metric (specifically, where knowing an individual is in the database poses a privacy risk), and  ...  We present a metric, δ-presence, that clearly links the quality of anonymization to the risk posed by inadequate anonymization.  ...  For cost metrics proposed so far, a high level generalization (e.g., T ) is more costly than a lower generalization (e.g., T ).  ... 
doi:10.1145/1247480.1247554 dblp:conf/sigmod/NergizAC07 fatcat:czkhi7tlczayfexz3qjymo3tku

Towards optimal k-anonymization

Tiancheng Li, Ninghui Li
2008 Data & Knowledge Engineering  
Through experiments on real census data, we show that more-flexible generalization schemes produce higher-quality anonymizations and the bottom-up works better for small k values and small number of quasi-identifer  ...  A major thread of research in this area aims at developing more flexible generalization schemes and more efficient searching algorithms to find better anonymizations (i.e., those that have less information  ...  For the same k value, the cost decreases for the more sophisticated generalization schemes.  ... 
doi:10.1016/j.datak.2007.06.015 fatcat:un2ulu3x5jdllfg54bi7wjadz4

Towards trajectory anonymization

Mehmet Ercan Nergiz, Maurizio Atzori, Yucel Saygin
2008 Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS - SPRINGL '08  
We present a utility metric that maximizes the probability of a good representation and propose trajectory anonymization techniques to address time and space sensitive applications.  ...  We provide privacy protection by defining trajectory k-anonymity, meaning every released information refers to at least k users/trajectories.  ...  Most clustering algorithms can easily be modified for k-anonymity by enforcing that the size of the clusters should be more than k (2, 33, 12, 1) .  ... 
doi:10.1145/1503402.1503413 dblp:conf/gis/NergizAS08 fatcat:7zcpieahunfw5nygpyso3jlthm

Outsourcing privacy-preserving social networks to a cloud

Guojun Wang, Qin Liu, Feng Li, Shuhui Yang, Jie Wu
2013 2013 Proceedings IEEE INFOCOM  
In the real world, companies would publish social networks to a third party, e.g., a cloud service provider, for marketing reasons.  ...  With this information, an attacker may re-identify the target from a k-anonymity social network with a probability higher than 1/k, where any node's 1-neighborhood graph is isomorphic with k − 1 other  ...  To obtain a reasonable randomization probability p, we first randomly generate a graph with N nodes and M edges.  ... 
doi:10.1109/infcom.2013.6567099 dblp:conf/infocom/WangLLY013 fatcat:ihwxn5snlffm7deecrhytrgtxu

A Differentiated Anonymity Algorithm for Social Network Privacy Preservation

Yuqin Xie, Mingchun Zheng
2016 Algorithms  
Devising methods to publish social network data in a form that affords utility without compromising privacy remains a longstanding challenge, while many existing methods based on k-anonymity algorithms  ...  Furthermore, we design and implement a differentiated k-anonymity l-diversity social network anonymity algorithm, which seeks to protect users' privacy in social networks and increase the usability of  ...  Figure 4 . 4 Last Figure 5 . 5 dataset (a) and Delicious dataset (b): costs for different k values.  ... 
doi:10.3390/a9040085 fatcat:yg5knfrcczc4fg5kp4uitauh74

A K-Anonymity Based Schema for Location Privacy Preservation

Fan Fei, Shu Li, Haipeng Dai, Chunhua Hu, Wanchun Dou, Qiang Ni
2017 IEEE Transactions on Sustainable Computing  
In view of this challenge, we propose a two-tier schema for the privacy preservation based on kanonymity principle meanwhile reduce the cost for privacy protection.  ...  In recent years, with the development of mobile devices, the location based services (LBSs) have become more and more prevailing and most applications installed on these devices call for location information  ...  Other metrics, such as k-anonymity [14] , t-closeness [15] , [16] , and other variations, measure the privacy level according to the size of anonymity set. The above metrics are uncertainty based.  ... 
doi:10.1109/tsusc.2017.2733018 dblp:journals/tsusc/FeiLDHDN19 fatcat:mf5lvhqmyvd5ppo4oyttaubari

Real-world K-Anonymity Applications: the KGen approach and its evaluation in Fraudulent Transactions [article]

Daniel De Pascale, Giuseppe Cascavilla, Damian A. Tamburri, Willem-Jan Van Den Heuvel
2022 arXiv   pre-print
K-Anonymity is a property for the measurement, management, and governance of the data anonymization.  ...  Many implementations of k-anonymity have been described in state of the art, but most of them are not able to work with a large number of attributes in a "Big" dataset, i.e., a dataset drawn from Big Data  ...  As discussed in section 2, there are two metrics for the evaluation of a single node, namely, (a) k-anonymity and (b) loss of information.  ... 
arXiv:2204.01533v1 fatcat:xbdsrwcbarfvjbscwz52rbecqa

A Survey on Methods, Attacks and Metric for Privacy Preserving Data Publishing

Kiran P, Kavya N.P
2012 International Journal of Computer Applications  
We have also discussed various attacks that may take place during anonymization. A comprehensive study of various metric used for measuring anonymity has also been discussed.  ...  In this paper, we provide a review of various methods for anonymization and analyze various disclosures that may happen in each of them.  ...  Iloss for the entire T* is given by ∑ ∈ Classification Metric (CM), is introduced by Iyengar [18] to optimize a k-anonymous dataset.  ... 
doi:10.5120/8521-2380 fatcat:fwpjo3yk2jftrhsfsg7klaa44y

k-Anonymous Query Scheme on the Internet of Things: a Zero Trust Architecture

2021 Journal of networking and network applications  
Based on the proposed k-anonymity scheme, the trade-offs between the achieved query-anonymity and various performance measures including, communication-cost, return-on-investment metric, path-length, and  ...  Thus, the paper firstly introduces a novel query k-anonymity scheme that countermeasures such a privacy threat.  ...  A reason for that must be related to the way that the piggy-back strategy collects sensor readings which incurs a cost that grows with the remainder of n/k.  ... 
doi:10.33969/j-nana.2021.010302 fatcat:wntb6bjbozd35mr5uq6ieo6u4i

Anonymizing Classification Data for Privacy Preservation

Benjamin C.M. Fung, Ke Wang, Philip S. Yu
2007 IEEE Transactions on Knowledge and Data Engineering  
In this paper, we propose a k-anonymization solution for classification.  ...  Previous work attempted to find an optimal k-anonymization that minimizes some data distortion metric.  ...  For this reason, our problem does not have a closed form cost metric, and an "optimal" solution to our problem is not necessarily an optimal k-anonymization based on a closed form cost metric, and vice  ... 
doi:10.1109/tkde.2007.1015 fatcat:op6drxswhzhk5hzursulhkzr3u

A Novel Location Privacy Preservation Method for Moving Object

Xu Zhang, Ying Xia, HaeYoung Bae
2015 International Journal of Security and Its Applications  
In this paper, we propose a new semantic privacy preservation method rely on the well-established k-anonymity and l-diversity privacy metrics for semantic cloaking.  ...  We also define a representative cloaking region which helps in communication cost reduction caused by user movement.  ...  Numerous privacy metric and scheme have been proposed in LBS privacy protection community including [1, 4] :  Query Privacy Metric -k-anonymity is the most popular metric used for LBS query privacy protection  ... 
doi:10.14257/ijsia.2015.9.2..01 fatcat:evrffzbnu5a2pnmoi7yt6nevka

K-Anonymization as Spatial Indexing: Toward Scalable and Incremental Anonymization

Tochukwu Iwuchukwu, David J. DeWitt, AnHai Doan, Jeffrey F. Naughton
2007 2007 IEEE 23rd International Conference on Data Engineering  
Finally, we show that the anonymizations generated by the R-tree approach do not sacrifice quality in their search for efficiency; in fact, by several previously proposed quality metrics, the compact partitioning  ...  In this paper we observe that k-anonymizing a data set is strikingly similar to building a spatial index over the data set, so similar in fact that classical spatial indexing techniques can be used to  ...  It is also reasonable to expect the execution costs for the compaction process to be relatively small when compared to actual anonymization costs as its basic operation is a single pass over each partition  ... 
doi:10.1109/icde.2007.369024 dblp:conf/icde/IwuchukwuDDN07 fatcat:semsw5i2gfhvnjanzp66bl7syi

Optimizing the design parameters of threshold pool mixes for anonymity and delay

David Rebollo-Monedero, Javier Parra-Arnau, Jordi Forné, Claudia Diaz
2014 Computer Networks  
Experimental results show that mix optimization may lead to substantial delay reductions for a desirable level of anonymity.  ...  Anonymous-communication systems emerge as a response against such traffic analysis threats. Mixes, and in particular threshold pool mixes, are a building block of anonymous communications systems.  ...  Acknowledgments We would like to thank the anonymous referees for their extremely valuable comments. This work was partly supported by the Spanish Government through projects  ... 
doi:10.1016/j.comnet.2014.04.007 fatcat:7fgnqqdionbwlljefng75hcrha
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