{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T15:25:33Z","timestamp":1751383533984,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030300470"},{"type":"electronic","value":"9783030300487"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-30048-7_37","type":"book-chapter","created":{"date-parts":[[2019,9,22]],"date-time":"2019-09-22T19:03:06Z","timestamp":1569178986000},"page":"639-655","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Differential Privacy of Hierarchical Census Data: An Optimization Approach"],"prefix":"10.1007","author":[{"given":"Ferdinando","family":"Fioretto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Van Hentenryck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,23]]},"reference":[{"key":"37_CR1","unstructured":"AAAS: New Privacy Protections Highlight the Value of Science Behind the 2020 census. \n                      https:\/\/www.aaas.org\/news\/new-privacy-protections-highlight-value-science-behind-2020-census\n                      \n                    . Accessed 23 Apr 2019"},{"key":"37_CR2","unstructured":"NBC News: Potential privacy lapse found in Americans\u2019 2010 census data. \n                      https:\/\/www.nbcnews.com\/news\/us-news\/potential-privacy-lapse-found-americans-2010-census-data-n972471\n                      \n                    . Accessed 23 Apr 2019"},{"key":"37_CR3","unstructured":"New York City Taxi Data. \n                      http:\/\/www.nyc.gov\/html\/tlc\/html\/about\/trip_record_data.shtml\n                      \n                    . Accessed 20 Apr 2019"},{"key":"37_CR4","unstructured":"NY Times: To Reduce Privacy Risks, the Census Plans to Report Less AccurateData. \n                      https:\/\/www.nytimes.com\/2018\/12\/05\/upshot\/to-reduce-privacy-risks-the-census-plans-to-report-less-accurate-data.html"},{"key":"37_CR5","doi-asserted-by":"crossref","unstructured":"Cormode, G., Procopiuc, C., Srivastava, D., Shen, E., Yu, T.: Differentially private spatial decompositions. In: 2012 IEEE 28th International Conference on Data Engineering, pp. 20\u201331. IEEE (2012)","DOI":"10.1109\/ICDE.2012.16"},{"key":"37_CR6","doi-asserted-by":"crossref","unstructured":"Dinur, I., Nissim, K.: Revealing information while preserving privacy. In: Proceedings of the Twenty-Second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 202\u2013210. ACM (2003)","DOI":"10.1145\/773153.773173"},{"key":"37_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/11681878_14","volume-title":"Theory of Cryptography","author":"C Dwork","year":"2006","unstructured":"Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: Halevi, S., Rabin, T. (eds.) TCC 2006. LNCS, vol. 3876, pp. 265\u2013284. Springer, Heidelberg (2006). \n                      https:\/\/doi.org\/10.1007\/11681878_14"},{"issue":"3\u20134","key":"37_CR8","first-page":"211","volume":"9","author":"C Dwork","year":"2013","unstructured":"Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Theoret. Comput. Sci. 9(3\u20134), 211\u2013407 (2013)","journal-title":"Theoret. Comput. Sci."},{"key":"37_CR9","doi-asserted-by":"crossref","unstructured":"Erlingsson, \u00da., Pihur, V., Korolova, A.: Rappor: randomized aggregatable privacy-preserving ordinal response. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1054\u20131067. ACM (2014)","DOI":"10.1145\/2660267.2660348"},{"key":"37_CR10","unstructured":"Fioretto, F., Lee, C., Van Hentenryck, P.: Constrained-based differential privacy for private mobility. In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1405\u20131413 (2018)"},{"issue":"1","key":"37_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10601-017-9274-1","volume":"23","author":"F Fioretto","year":"2018","unstructured":"Fioretto, F., Pontelli, E., Yeoh, W., Dechter, R.: Accelerating exact and approximate inference for (distributed) discrete optimization with GPUs. Constraints 23(1), 1\u201343 (2018)","journal-title":"Constraints"},{"key":"37_CR12","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/978-3-319-93031-2_15","volume-title":"Integration of Constraint Programming, Artificial Intelligence, and Operations Research","author":"Ferdinando Fioretto","year":"2018","unstructured":"Fioretto, F., Van Hentenryck, P.: Constrained-based differential privacy: releasing optimal power flow benchmarks privately. In: Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR), pp. 215\u2013231 (2018)"},{"issue":"6","key":"37_CR13","doi-asserted-by":"publisher","first-page":"1673","DOI":"10.1137\/09076828X","volume":"41","author":"A Ghosh","year":"2012","unstructured":"Ghosh, A., Roughgarden, T., Sundararajan, M.: Universally utility-maximizing privacy mechanisms. SIAM J. Comput. 41(6), 1673\u20131693 (2012)","journal-title":"SIAM J. Comput."},{"key":"37_CR14","doi-asserted-by":"crossref","unstructured":"Golle, P.: Revisiting the uniqueness of simple demographics in the US population. In: Proceedings of the 5th ACM Workshop on Privacy in Electronic Society, pp. 77\u201380. ACM (2006)","DOI":"10.1145\/1179601.1179615"},{"issue":"1\u20132","key":"37_CR15","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.14778\/1920841.1920970","volume":"3","author":"M Hay","year":"2010","unstructured":"Hay, M., Rastogi, V., Miklau, G., Suciu, D.: Boosting the accuracy of differentially private histograms through consistency. Proc. VLDB Endow. 3(1\u20132), 1021\u20131032 (2010)","journal-title":"Proc. VLDB Endow."},{"key":"37_CR16","doi-asserted-by":"crossref","unstructured":"Huang, D., Han, S., Li, X., Yu, P.S.: Orthogonal mechanism for answering batch queries with differential privacy. In: Proceedings of the 27th International Conference on Scientific and Statistical Database Management, p. 24. ACM (2015)","DOI":"10.1145\/2791347.2791378"},{"key":"37_CR17","doi-asserted-by":"crossref","unstructured":"Kuo, Y.H., Chiu, C.C., Kifer, D., Hay, M., Machanavajjhala, A.: Differentially private hierarchical group size estimation. arXiv preprint \n                      arXiv:1804.00370\n                      \n                     (2018)","DOI":"10.14778\/3236187.3236202"},{"issue":"5","key":"37_CR18","doi-asserted-by":"publisher","first-page":"341","DOI":"10.14778\/2732269.2732271","volume":"7","author":"C Li","year":"2014","unstructured":"Li, C., Hay, M., Miklau, G., Wang, Y.: A data-and workload-aware algorithm for range queries under differential privacy. Proc. VLDB Endow. 7(5), 341\u2013352 (2014)","journal-title":"Proc. VLDB Endow."},{"key":"37_CR19","doi-asserted-by":"crossref","unstructured":"Li, T., Li, N.: On the tradeoff between privacy and utility in data publishing. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 517\u2013526. ACM (2009)","DOI":"10.1145\/1557019.1557079"},{"key":"37_CR20","unstructured":"McSherry, F., Talwar, K.: Mechanism design via differential privacy. In: 48th Annual IEEE Symposium on Foundations of Computer Science, 2007, FOCS 2007, pp. 94\u2013103. IEEE (2007)"},{"issue":"14","key":"37_CR21","doi-asserted-by":"publisher","first-page":"1954","DOI":"10.14778\/2556549.2556576","volume":"6","author":"W Qardaji","year":"2013","unstructured":"Qardaji, W., Yang, W., Li, N.: Understanding hierarchical methods for differentially private histograms. Proc. VLDB Endow. 6(14), 1954\u20131965 (2013)","journal-title":"Proc. VLDB Endow."},{"issue":"05","key":"37_CR22","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1142\/S0218488502001648","volume":"10","author":"L Sweeney","year":"2002","unstructured":"Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty, Fuzziness Knowl.-Based Syst. 10(05), 557\u2013570 (2002)","journal-title":"Int. J. Uncertainty, Fuzziness Knowl.-Based Syst."},{"issue":"8","key":"37_CR23","first-page":"1","volume":"1","author":"ADP Team","year":"2017","unstructured":"Team, A.D.P.: Learning with privacy at scale. Apple Mach. Learn. J. 1(8), 1\u201325 (2017)","journal-title":"Apple Mach. Learn. J."},{"key":"37_CR24","unstructured":"U.S. Census Bureau: 2010 census summary file 1: census of population and housing, technical documentation (2012). \n                      https:\/\/www.census.gov\/prod\/cen2010\/doc\/sf1.pdf"},{"key":"37_CR25","unstructured":"Winkler, W.: Single ranking micro-aggregation and re-identification. Statistical Research Division report RR 2002\/8 (2002)"}],"container-title":["Lecture Notes in Computer Science","Principles and Practice of Constraint Programming"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-30048-7_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,25]],"date-time":"2019-09-25T16:07:48Z","timestamp":1569427668000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-30048-7_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030300470","9783030300487"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-30048-7_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Principles and Practice of Constraint Programming","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Stamford, CT","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cp2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cp2019.a4cp.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"118","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}