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Differential privacy with δ-neighbourhood for spatial and dynamic datasets

Chengfang Fang, Ee-Chien Chang
2014 Proceedings of the 9th ACM symposium on Information, computer and communications security - ASIA CCS '14  
Differential privacy provides a strong guarantee in protecting privacy of individuals who contributed to a published dataset.  ...  For dynamic datasets, while there are known negative results on the standard differential privacy, it is possible to continuously and indefinitely publish under δ-neighbourhood by reusing the privacy budgets  ...  PUBLISHING SPATIAL DATASET Although an -differentially private mechanism under the standard neighbourhood is also -differentially private under δ-neighbourhood, it may not achieve our intention of investing  ... 
doi:10.1145/2590296.2590320 dblp:conf/ccs/FangC14 fatcat:6ogho2wslfgddizbqd2jmuudsa

Multidomain Fusion Data Privacy Security Framework

Jing Yang, Lianwei Qu, Yong Wang, James Ying
2021 Wireless Communications and Mobile Computing  
Second, combine them with the different modal histograms to build multimodal histograms. Finally, we propose a privacy protection model to ensure the security of data publishing.  ...  However, this puts forward new requirements for the security of data publishing.  ...  Although the paper [16] [17] [18] [19] [20] fully improved the histogram data publishing algorithm based on differential privacy, the data availability after privacy protection is not better when publishing  ... 
doi:10.1155/2021/8492223 fatcat:2qoi7o3kujav5ddvvxm2lgulo4

Histogram Publishing Method Based on Differential Privacy

Xin Liu, Shengen Li
2018 DEStech Transactions on Computer Science and Engineering  
The distribution of differential privacy histograms based on groupings has drawn much attention from researchers and how to balance the approximation error caused by the group mean with the Laplace error  ...  This paper proposes a method of APG (Affinity Propagation Clustering and Grouping algorithm) based on clustering grouping to distribute differential privacy histogram, which can effectively balance the  ...  HISTOGRAM PUBLISHING METHOD UNDER DIFFERENTIAL PRIVACY The framework of the APG method in this paper is shown in figure 2 .  ... 
doi:10.12783/dtcse/csse2018/24489 fatcat:gquwss5p4zbppfo4io6wio5puu

Publishing Location Dataset Differential Privately with Isotonic Regression [article]

Chengfang Fang, Ee-Chien Chang
2011 arXiv   pre-print
We consider the problem of publishing location datasets, in particular 2D spatial pointsets, in a differentially private manner.  ...  The publishing process is simple from the publisher's point of view: the publisher just needs to map the data, sort them, group them, add Laplace noise and publish the dataset.  ...  Note that a mechanism that achieves differential privacy under replacement neighborhood can be converted to one that achieves privacy under the welladopted neighborhood.  ... 
arXiv:1111.6677v1 fatcat:nmetfenuyvd5pdiaaxypq5quoa

PrivTree

Jun Zhang, Xiaokui Xiao, Xing Xie
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
Furthermore, h cannot be directly tuned based on D; otherwise, the choice of h itself reveals private information and violates differential privacy.  ...  Given a set D of tuples defined on a domain Ω, we study differentially private algorithms for constructing a histogram over Ω to approximate the tuple distribution in D.  ...  ADDITIONAL RELATED WORK In Sections 3.1, 4.3, and 6, we have introduced the states-of- the-art solutions [6, 12, 30, 41, 42, 48, 50] for publishing spatial and sequence data under differential privacy  ... 
doi:10.1145/2882903.2882928 dblp:conf/sigmod/ZhangXX16 fatcat:dheqm5gztneefcudvltcgz2ffm

APRS: a privacy-preserving location-aware recommender system based on differentially private histogram

Sheng Gao, Xindi Ma, Jianming Zhu, Jianfeng Ma
2017 Science China Information Sciences  
APRS: a privacy-preserving location-aware recommender system based on differentially private histogram.  ...  The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.  ...  Because the sorting operation is conducted on differentially private histogram bins, it does not violate the differential privacy and reveal any extra privacy any more.  ... 
doi:10.1007/s11432-017-9222-7 fatcat:gxaiwguofzhq7ln5o3gihnl554

PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions [article]

Jun Zhang and Xiaokui Xiao and Xing Xie
2016 arXiv   pre-print
Given a set D of tuples defined on a domain Omega, we study differentially private algorithms for constructing a histogram over Omega to approximate the tuple distribution in D.  ...  As concrete examples, we demonstrate an application of PrivTree in modelling spatial data, and show that it can also be extended to handle sequence data (where the decision in sub-domain splitting is not  ...  ADDITIONAL RELATED WORK In Sections 3.1, 4.3, and 6, we have introduced the states-ofthe-art solutions [6, 12, 30, 41, 42, 48, 50] for publishing spatial and sequence data under differential privacy.  ... 
arXiv:1601.03229v2 fatcat:rcdssuer5ncmnnejlavltyrsd4

Spatio-temporal Trajectory Dataset Privacy Based on Network Traffic Control [article]

Qilong Han, Qianqian Chen, Kejia Zhang, Xiaojiang Du, Nadra Guizani
2018 arXiv   pre-print
Based on similarity point aggregation reconstruction ideas and a prefix tree model, we proposed a hybrid publishing method of differential privacy spatiotemporal trajectory data sets APTB.  ...  In this paper, we consider a network traffic control system as a trusted third party and use differential privacy for protecting more personal trajectory data.  ...  Differential privacy algorithms [7, 8] such as prefix and n-gram are published for spatial trajectory data sets, and differential privacy algorithms such as GST for spatio-temporal trajectory data sets  ... 
arXiv:1804.02052v1 fatcat:zylq7slqu5febhyvzlos4dzsuu

Adaptive Differentially Private Histogram of Low-Dimensional Data [chapter]

Chengfang Fang, Ee-Chien Chang
2012 Lecture Notes in Computer Science  
We want to publish low-dimensional points, for example 2D spatial points, in a differentially private manner.  ...  For instance, Xiao et al. [28] proposes publishing wavelet coefficients of an equi-width histogram, which can be viewed as publishing a series of equi-width histograms with different bin-widths, and is  ...  Differential privacy with this definition of neighborhood is known as the bounded differential privacy [6, 13] .  ... 
doi:10.1007/978-3-642-31680-7_9 fatcat:ikvnfk77qbddxcxsps5u2czlcq

Differential Privacy in Practice

Hiep H. Nguyen, Jong Kim, Yoonho Kim
2013 Journal of Computing Science and Engineering  
We briefly review the problem of statistical disclosure control under differential privacy model, which entails a formal and ad omnia privacy guarantee separating the utility of the database and the risk  ...  Promises of differential privacy help to relieve concerns of privacy loss, which hinder the release of community-valuable data.  ...  Histogram sanitization under a formal privacy was introduced early by Chawla et al. [34] .  ... 
doi:10.5626/jcse.2013.7.3.177 fatcat:xrcbyxpzfvh2tfdrr5572rdnku

Non-interactive differential privacy

David Leoni
2012 Proceedings of the First International Workshop on Open Data - WOD '12  
Differential privacy stands out as a model that provides strong formal guarantees about the anonymity of the participants in a sanitized database.  ...  This paper covers such breakthrough discoveries, by reviewing applications of differential privacy for non-interactive publication of anonymized real-life datasets.  ...  We indicate such condition as |D1∆D2| = 1 DIFFERENTIAL PRIVACY Randomized algorithms to publish sensitive data are called mechanisms.  ... 
doi:10.1145/2422604.2422611 dblp:conf/wod/Leoni12 fatcat:tdfnvwiqybe7pos2z4sc4unk7q

Non-Interactive Differential Privacy: a Survey [article]

David Leoni
2012 arXiv   pre-print
Differential privacy stands out as a model that provides strong formal guarantees about the anonymity of the participants in a sanitized database.  ...  This paper covers such breakthrough discoveries, by reviewing applications of differential privacy for non-interactive publication of anonymized real-life datasets.  ...  We indicate such condition as |D1∆D2| = 1 DIFFERENTIAL PRIVACY Randomized algorithms to publish sensitive data are called mechanisms.  ... 
arXiv:1205.2726v1 fatcat:shps24vi2jg3fibknsmltsziky

Differentially Private High-Dimensional Data Publication via Markov Network

Wei Zhang, Jingwen Zhao, Fengqiong Wei, Yunfang Chen
2019 EAI Endorsed Transactions on Security and Safety  
We then take advantage of approximate inference to calculate the joint distribution of high-dimensional data under differential privacy to figure out the computational and spatial complexity of accurate  ...  Extensive experiments on real datasets demonstrate that our solution makes the published high-dimensional synthetic datasets more efficient under the guarantee of differential privacy.  ...  Dwork [8] proposed an early representative method, which combines with Laplace mechanism to publish an equalwidth histogram under differential privacy guarantee.  ... 
doi:10.4108/eai.29-7-2019.159626 fatcat:uakxu2jf2vgnlp2nnwmh6cc63q

Empirical privacy and empirical utility of anonymized data

G. Cormode, C. M. Procopiuc, Entong Shen, D. Srivastava, Ting Yu
2013 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW)  
Consequently, we are able to place different privacy models including differential privacy and early syntactic models on the same scale, and compare their privacy/utility tradeoff.  ...  Early models (kanonymity and -diversity) are now thought to offer insufficient privacy. Noise-based methods like differential privacy are seen as providing stronger privacy, but less utility.  ...  In this region either -diversity or t-closeness can outperform differential privacy under these metrics as shown in both plots.  ... 
doi:10.1109/icdew.2013.6547431 dblp:conf/icde/CormodePSSY13 fatcat:w5v5hr4nhzca3htc2ide3ta3uy

DATA PUBLICATION BASED ON DIFFERENTIAL PRIVACY IN V2G NETWORK

Xiong LIU, Haiqing LIU
2021 International journal of electronics engineering and application  
In response to this problem, this paper proposes a dynamic data publishing algorithm based on differential privacy.  ...  Compared with traditional input data set noise injection methods, the proposed algorithm improves data availability and reduces publishing errors  ...  [8] combined autoregressive integrated moving average model and dynamic sliding window counting, and proposed a data stream differential privacy histogram publishing algorithm ASDP-HPA, which improves  ... 
doi:10.30696/ijeea.ix.ii.2021.45-53 fatcat:ppgrrvxdkrfr5ndyakptz66aeu
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