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Histogram Estimation under User-level Privacy with Heterogeneous Data [article]

Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser
2022 arXiv   pre-print
We study the problem of histogram estimation under user-level differential privacy, where the goal is to preserve the privacy of all entries of any single user.  ...  While there is abundant literature on this classical problem under the item-level privacy setup where each user contributes only one data point, little has been known for the user-level counterpart.  ...  Conclusion and discussion We study the problem of estimating a population-level histogram under user-level privacy with heterogeneous data.  ... 
arXiv:2206.03008v1 fatcat:5ez5zrsa3bfhzcx7fs42fjx6a4

Local differential privacy for unbalanced multivariate nominal attributes

Xuejie Feng, Chiping Zhang
2020 Human-Centric Computing and Information Sciences  
Extension simulations on two different data sets with multivariate nominal attributes demonstrated that the scheme proposed in this paper can significantly reduce the estimation error under the premise  ...  Particularly, with high-dimensional heterogeneous data (data with unbalanced multivariate nominal attributes), there are many hidden rules and much hidden information behind the data that can be mined  ...  (Project name: Big data and business intelligence social service innovation team).  ... 
doi:10.1186/s13673-020-00233-x fatcat:nmn6txwzjva6beboaxlvnjdhra

Histogram Publication over Numerical Values under Local Differential Privacy

Xu Zheng, Ke Yan, Jingyuan Duan, Wenyi Tang, Ling Tian, Yingjie Wang
2021 Wireless Communications and Mobile Computing  
Local differential privacy has been considered the standard measurement for privacy preservation in distributed data collection.  ...  However, the histogram publication of numerical values, containing abundant and crucial clues for the whole dataset, has not been thoroughly considered under this measurement.  ...  This is extremely unwillingness when many consumers request histograms with heterogeneous intervals.  ... 
doi:10.1155/2021/8886255 fatcat:fdgkm5ehtvfg5izhhsmmgxjgra

A Sampling-Based Method for Highly Efficient Privacy-Preserving Data Publication

Guoming Lu, Xu Zheng, Jingyuan Duan, Ling Tian, Xia Wang, Lin Wang
2021 Wireless Communications and Mobile Computing  
Specifically, two sampling-based algorithms are proposed for the histogram publication, which is an important statistic for data analysis.  ...  With the emergence of diversified smart devices and applications, data held by individuals becomes more pervasive and nontrivial for publication.  ...  We assume that data consumers request for the histogram of incoming levels with heterogeneous granularity.  ... 
doi:10.1155/2021/6648775 fatcat:3aoekyz5nnbtho66xv4yooapdy

Combinational Randomized Response Mechanism for Unbalanced Multivariate Nominal Attributes

Xuejie Feng, Chiping Zhang, Jing Li, Linlin Dai
2020 IEEE Access  
work was supported by the Construction team project of the introduction and cultivation of young innovative talents in Colleges and universities of Shandong Province of China, 2019 (Project name: Big data  ...  We compared the local differential privacy mechanism CRR proposed in this paper with BRR, OBRR, MRR, and OMRR for the different data sets HDD (n = 1000, 10000) and LDD (n = 1000, 10000).  ...  This is equivalent to finding the optimal privacy budget allocation scheme in BRR. At this time, the differential privacy mechanism is called OBRR. Similarly, when h = l, we call it OMRR.  ... 
doi:10.1109/access.2020.3013446 fatcat:ghzttva4ubftvbw5mrqpzrdcnm

Optimization of Privacy-Utility Trade-offs under Informational Self-determination [article]

Thomas Asikis, Evangelos Pournaras
2018 arXiv   pre-print
Nonetheless they can also be applied autonomously by each user or decided under the influence of (monetary) incentives (heterogeneous data sharing).  ...  The framework computes a broad spectrum of such trade-offs that form privacy-utility trajectories under homogeneous and heterogeneous data sharing.  ...  Heterogeneous system evaluation In an heterogeneous system, the framework performance is evaluated under the use of different privacy settings from each user.  ... 
arXiv:1710.03186v2 fatcat:6g53qtkfrbazfeaz4l26rfe7vi

Optimization of privacy-utility trade-offs under informational self-determination

Thomas Asikis, Evangelos Pournaras
2018 Future generations computer systems  
Heterogeneous system evaluation In an heterogeneous system, the framework performance is evaluated under the use of different privacy settings from each user.  ...  (ii) A formal proof on how high utility can be achieved under informational self-determination (heterogeneous data sharing) originated from the diversity in the privacy settings selected by the users.  ... 
doi:10.1016/j.future.2018.07.018 fatcat:knyayh4gybfcdddtts7i33qe5e

An Introduction to Federated Computation

Akash Bharadwaj, Graham Cormode
2022 Proceedings of the 2022 International Conference on Management of Data  
Federated Computation is an emerging area that seeks to provide stronger privacy for user data, by performing large scale, distributed computations where the data remains in the hands of users.  ...  data.  ...  • The problem of computing a histogram (set of counts) from a data set is one of the most heavily studied under the model of differential privacy.  ... 
doi:10.1145/3514221.3522561 fatcat:og5gh5asqrgfllxa7cuex6y6gi

One-sided Differential Privacy [article]

Stelios Doudalis, Ios Kotsogiannis, Samuel Haney, Ashwin Machanavajjhala, Sharad Mehrotra
2017 arXiv   pre-print
In this paper, we study the problem of privacy-preserving data sharing, wherein only a subset of the records in a database are sensitive, possibly based on predefined privacy policies.  ...  The sample can be used to support applications that must output true data, and is well suited for publishing complex types of data, e.g. trajectories.  ...  In prior work, heterogeneous DP [4] and personalized differential privacy (PDP) [21] have tried to take advantage of different privacy levels between records.  ... 
arXiv:1712.05888v1 fatcat:32gl57ogpnahlhchj5hel35j4q

Multimedia security and privacy protection in the internet of things: research developments and challenges

Jiankun Hu, Nickson M. Karie, Song Wang, Wencheng Yang
2022 International Journal of Multimedia Intelligence and Security  
First, we classify multimedia data into different types and security levels according to application areas.  ...  In this paper, we conduct a comprehensive survey on multimedia data security and privacy protection in the IoT.  ...  and privacy level of multimedia data.  ... 
doi:10.1504/ijmis.2022.10044461 fatcat:xdliezm2kbe3vkrpgnso74xtba

A Comprehensive Survey on Local Differential Privacy toward Data Statistics and Analysis

Teng Wang, Xuefeng Zhang, Jingyu Feng, Xinyu Yang
2020 Sensors  
Local differential privacy (LDP) was proposed as an excellent and prevalent privacy model with distributed architecture, which can provide strong privacy guarantees for each user while collecting and analyzing  ...  However, extensive statistics and analysis of such data will seriously threaten the privacy of participating users.  ...  the data with distinct sensitivity levels.  ... 
doi:10.3390/s20247030 pmid:33302517 pmcid:PMC7763193 fatcat:25iufaivynabdftrzq4rzxsz2e

The Impact of Privacy Policy on the Auction Market for Online Display Advertising

Garrett A. Johnson
2013 Social Science Research Network  
I consider three privacy policies that vary by the degree of user choice.  ...  This paper estimates the financial impact of privacy policies on the online display ad industry by applying an empirical model to a proprietary auction dataset.  ...  This utility function resembles that of Krasnokutskaya (2011) though with user-level rather than auction-level unobserved heterogeneity.  ... 
doi:10.2139/ssrn.2333193 fatcat:ag656kffl5fspnh56z4oobyhq4

Privacy-protecting video surveillance

Jehan Wickramasuriya, Mohanned Alhazzazi, Mahesh Datt, Sharad Mehrotra, Nalini Venkatasubramanian, Nasser Kehtarnavaz, Phillip A. Laplante
2005 Real-Time Imaging IX  
Radio-frequency Identification) with video streams and an access control framework in order to make decisions about how and when to display the individuals under surveillance.  ...  This video surveillance system is a particular instance of a more general paradigm of privacy-protecting data collection.  ...  ACKNOWLEDGMENTS Support of this research by the National Science Foundation under Award Numbers 0331707 and 0331690 is gratefully acknowledged.  ... 
doi:10.1117/12.587986 fatcat:g32ccpuv4raujpwo5l2huhjbcq

SHARE: system design and case studies for statistical health information release

J. Gardner, L. Xiong, Y. Xiao, J. Gao, A. R. Post, X. Jiang, L. Ohno-Machado
2013 JAMIA Journal of the American Medical Informatics Association  
Results Experimental results indicate that SHARE can deal with heterogeneous data present in medical data, and that the released statistics are useful.  ...  Materials and Methods SHARE releases statistical information in electronic health records with differential privacy, a strong privacy framework for statistical data release.  ...  Given a userissued query, an estimation component can answer the query using the subcube histogram or apply inference or estimation techniques to boost the accuracy further using both histograms. 39 41  ... 
doi:10.1136/amiajnl-2012-001032 pmid:23059729 pmcid:PMC3555328 fatcat:ghrwohia6ve2za5cv3vx5quy7u

Quantifying Privacy Loss of Human Mobility Graph Topology

Dionysis Manousakas, Cecilia Mascolo, Alastair R. Beresford, Dennis Chan, Nikhil Sharma
2018 Proceedings on Privacy Enhancing Technologies  
and edge weights corresponding to probability estimates of movements between these places.  ...  We then show that our distance metrics, while imperfect predictors, perform significantly better than a random strategy and therefore our approach represents a significant loss in privacy.  ...  Under this policy, the amount of privacy for each user is proportional to the size of the population.  ... 
doi:10.1515/popets-2018-0018 dblp:journals/popets/ManousakasMBCS18 fatcat:j4o4pss6ybbidgppzt6cbqbo4i
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