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The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy

Cynthia Dwork, Jonathan Ullman
2018 Journal of Privacy and Confidentiality  
In this note we discuss the (overly) simple problem of allowing a trusted analyst to choose an ""interesting" statistic for popular release (the actual computation of the chosen statistic will be carried  ...  Differential Privacy is a popular technology for privacy-preserving analysis of large datasets.  ...  This reflects both the relative youth of the field of differentially private data analysis -in a nutshell, there are things we do not yet know how to do -and lack of training among the social scientists  ... 
doi:10.29012/jpc.687 fatcat:efzkvh24dfc45guyw3xt6em5wy

Analyzing Behavioral Big Data: Methodological, Practical, Ethical, and Moral Issues

Galit Shmueli
2016 Social Science Research Network  
The term "Big Data" evokes emotions ranging from excitement to exasperation in the statistics community.  ...  I focus on Behavioral Big Data (BBD), or very large and rich multidimensional datasets on human behaviors, actions and interactions, which have become available to companies, governments, and researchers  ...  Special thanks to Steve Fienberg, Ron Kenett, Boaz Shmueli, and Alon Wolf for their comments and suggestions on an earlier draft of the paper.  ... 
doi:10.2139/ssrn.2736189 fatcat:5k27h77swbczlnj6qkjs5cxgia

A system for collecting and analyzing experience-sampling data

Simon Dennis, Hyungwook Yim, Paul Garrett, Vishnu Sreekumar, Ben Stone
2019 Behavior Research Methods  
In addition, machine-learning classifiers are run to identify aspects of the audio data such as voice and traffic.  ...  The augmented data are available to participants in the form of a keyword search interface, as well as via several visualization mechanisms.  ...  Analyzing data One of the most challenging issues when constructing a privacy-preserving data analysis system is how to allow researchers to conduct analyses when they are not permitted to see the data  ... 
doi:10.3758/s13428-019-01260-y fatcat:u2f2sw5nqzgpnbuvjix3d66l7a

An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices

John M. Abowd, Ian M. Schmutte
2019 The American Economic Review  
Recognizing this as a resource allocation problem, we propose an economic solution: operate where the marginal cost of increasing privacy equals the marginal benefit.  ...  Our model of production, from computer science, assumes data are published using an efficient differentially private algorithm.  ...  App. 10 House of Representatives. These methods were upheld in Utah v. Evans (U.S. Supreme Court 2002) .  ... 
doi:10.1257/aer.20170627 fatcat:dtjkeitlqnfetetq2vkya3jmga

(Almost) All of Entity Resolution [article]

Olivier Binette, Rebecca C. Steorts
2022 arXiv   pre-print
Whether the goal is to estimate the number of people that live in a congressional district, to estimate the number of individuals that have died in an armed conflict, or to disambiguate individual authors  ...  In this article, we review motivational applications and seminal papers that have led to the growth of this area.  ...  In the context of human rights applications, the Human Rights Data Analysis Group (HRDAG) also uses rule-based systems as part of the blocking stage of their entity resolution pipeline.  ... 
arXiv:2008.04443v3 fatcat:6tunuro7afhmbpambcn2bk32ly

Privacy in the Genomic Era

Muhammad Naveed, Erman Ayday, Ellen W. Clayton, Jacques Fellay, Carl A. Gunter, Jean-Pierre Hubaux, Bradley A. Malin, Xiaofeng Wang
2015 ACM Computing Surveys  
The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy.  ...  This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward  ...  ACKNOWLEDGMENTS We thank Aston Zhang and Ji Young Chun for their help with conducting the opinion poll; all the participants for their participation in our survey; the IRB of UIUC in general and Dustin  ... 
doi:10.1145/2767007 pmid:26640318 pmcid:PMC4666540 fatcat:2s4nhu2d6vgrtiebdg5qeognbi

Multiple Systems Estimation (or Capture-Recapture Estimation) to Inform Public Policy

Sheila M. Bird, Ruth King
2018 Annual Review of Statistics and Its Application  
Applications of estimating population sizes range from estimating human or ecological population size within regions or countries to estimating the hidden number of civilian casualties in war.  ...  Theory 21:235-46 Validation of gender and age-group interaction for people who inject drugs. King R, Bird SM, Overstall A, Hay G, Hutchinson SJ. 2014.  ...  To aid in the analysis of such data, a range of computer packages has been developed.  ... 
doi:10.1146/annurev-statistics-031017-100641 pmid:30046636 pmcid:PMC6055983 fatcat:oqlq5jgxnjfwbjjwafx6yddw7y

Privacy in the Genomic Era [article]

Muhammad Naveed, Erman Ayday, Ellen W. Clayton, Jacques Fellay, Carl A. Gunter, Jean-Pierre Hubaux, Bradley A. Malin, XiaoFeng Wang
2015 arXiv   pre-print
The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy.  ...  This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward  ...  VI.A Re-identification Threats Re-identification is probably the most extensively studied privacy risk in dissemination and analysis of human genomic data.  ... 
arXiv:1405.1891v3 fatcat:5ax5htkxmjbezf4zvw2y3n3q4i

Really Useful Synthetic Data – A Framework to Evaluate the Quality of Differentially Private Synthetic Data [article]

Christian Arnold, Marcel Neunhoeffer
2021 arXiv   pre-print
Recent advances in generating synthetic data that allow to add principled ways of protecting privacy -- such as Differential Privacy -- are a crucial step in sharing statistical information in a privacy  ...  Acknowledging that data quality is a subjective concept, we develop a framework to evaluate the quality of differentially private synthetic data from an applied researcher's perspective.  ...  They allow in-depth understanding of socio-economic issues by studying relationships and interactions among phenomena.  ... 
arXiv:2004.07740v2 fatcat:ar35f4jc75frnbwax3pwgzi32u

Providing Access to Confidential Research Data Through Synthesis and Verification: An Application to Data on Employees of the U.S. Federal Government [article]

Andrés F. Barrientos, Alexander Bolton, Tom Balmat, Jerome P. Reiter, John M. de Figueiredo, Ashwin Machanavajjhala, Yan Chen, Charley Kneifel, Mark DeLong
2018 arXiv   pre-print
We illustrate the integrated use of synthetic data plus verification via analysis of differentials in pay by race.  ...  that allows them to assess the quality of inferences from the synthetic data.  ...  The OPM data are valuable because they allow researchers to investigate many key questions in the study of human capital in large organizations and government organizations in particular.  ... 
arXiv:1705.07872v2 fatcat:bqenh3aopve7focahkan2edjku

Avoiding Disclosure of Individually Identifiable Health Information

Sergio I. Prada, Claudia González-Martínez, Joshua Borton, Johannes Fernandes-Huessy, Craig Holden, Elizabeth Hair, and Tim Mulcahy
2011 SAGE Open  
The views expressed in this article are those of the authors and do not necessarily reflect the views of the U.S.  ...  Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.  ...  To sidestep this issue, Dwork (2006) defines differential privacy and shows that this type of privacy can be implemented and formally proven.  ... 
doi:10.1177/2158244011431279 fatcat:q7vftlzwgbeldghz2daqg5dq7y

Privacy-preserving data publishing

Benjamin C. M. Fung, Ke Wang, Rui Chen, Philip S. Yu
2010 ACM Computing Surveys  
ACKNOWLEDGMENTS We sincerely thank the reviewers of this manuscript for greatly improving the quality of this survey.  ...  The key issues were how to modify the data and how to recover the data mining result from the modified data.  ...  Dwork [2008] further showed that the notion of differential privacy is applicable to both interactive and noninteractive query models, discussed in Sections 1.1 and 8.1; refer to Dwork [2008] for a  ... 
doi:10.1145/1749603.1749605 fatcat:ivbwule7bjafvmdvh236gbwryu

Towards a Modern Approach to Privacy-Aware Government Data Releases

Micah Altman, Urs Gasser
2016 Social Science Research Network  
Because much of the data they release pertains to individuals, agencies rely on various standards and interventions to protect privacy interests while supporting a range of beneficial uses of the data.  ...  These observations demonstrate the need for a more systematic approach to privacy analysis and also suggest a new way forward.  ...  To enable interactive analysis of the data, an intermediate level of access could be set up through a privacy-aware model server.  ... 
doi:10.2139/ssrn.2779266 fatcat:gokuyvoawrdvfienwdbwo2qbfq

The 2020 Census Disclosure Avoidance System TopDown Algorithm [article]

John M. Abowd and Robert Ashmead and Ryan Cumings-Menon and Simson Garfinkel and Micah Heineck and Christine Heiss and Robert Johns and Daniel Kifer and Philip Leclerc and Ashwin Machanavajjhala and Brett Moran and William Sexton and Matthew Spence and Pavel Zhuravlev
2022 arXiv   pre-print
The algorithm then creates noisy versions of key queries on the data, referred to as measurements, using zero-Concentrated Differential Privacy.  ...  Another key aspect of the TDA are invariants, statistics that the Census Bureau has determined, as matter of policy, to exclude from the privacy-loss accounting.  ...  Introduction Differential privacy (henceforth DP) is considered the gold standard in privacy-protected data publication-it allows organizations to collect and publish statistics about groups of people  ... 
arXiv:2204.08986v1 fatcat:bv5ow3lqqzbudjpi5kjdyuxdum

Privacy and Security in the Genomic Era

Erman Ayday, Jean-Pierre Hubaux
2016 Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security - CCS'16  
The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy.  ...  This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward  ...  (IRB) of UIUC in general and Dustin Yocum in particular for a quick approval of our survey and subsequent changes; and Jeanne-Pascale Simon, Zhicong Huang and Jean-Louis Raisaro for their useful comments  ... 
doi:10.1145/2976749.2976751 dblp:conf/ccs/AydayH16 fatcat:kpmg6s66ordppcl5blaqjv2blm
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