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Internet Technol."],"published-print":{"date-parts":[[2018,5,31]]},"abstract":"<jats:p>\n            Conventional private data publication schemes are targeted at publication of sensitive datasets either after the\n            <jats:italic>k<\/jats:italic>\n            -anonymization process or through differential privacy constraints. Typically these schemes are designed with the objective of retaining as much utility as possible for the aggregate queries while ensuring the privacy of the individual records. Such an approach, though suitable for publishing aggregate information as public datasets, is inapplicable when users have different levels of access to the same data. We argue that existing schemes either result in increased disclosure of private information or lead to reduced utility when some users have more access privileges than the others. In this article, we present an anonymization framework for publishing large datasets with the goals of providing different levels of utility to the users based on their access privilege levels. We design and implement our proposed multilevel utility-controlled anonymization schemes in the context of large association graphs considering three levels of user utility, namely, (1) users having access to only the graph structure, (2) users having access to the graph structure and aggregate query results, and (3) users having access to the graph structure, aggregate query results, and individual associations. Our experiments on real large association graphs show that the proposed techniques are effective and scalable and yield the required level of privacy and utility for each user privacy and access privilege level.\n          <\/jats:p>","DOI":"10.1145\/3125622","type":"journal-article","created":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T16:40:01Z","timestamp":1519404001000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Privacy-Preserving Publishing of Multilevel Utility-Controlled Graph Datasets"],"prefix":"10.1145","volume":"18","author":[{"given":"Balaji","family":"Palanisamy","sequence":"first","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Liu","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyang","family":"Wang","sequence":"additional","affiliation":[{"name":"Louisiana State University, Baton Rouge, LA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,2,22]]},"reference":[{"volume-title":"International Conference on Very Large Databases (VLDB\u20195).","year":"2005","author":"Aggarwal C.","key":"e_1_2_1_1_1"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242598"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687714"},{"volume-title":"International Conference on Very Large Databases (VLDB\u201911)","year":"2011","author":"Chen R.","key":"e_1_2_1_4_1"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920972"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.14778\/1453856.1453947"},{"key":"e_1_2_1_7_1","unstructured":"R. A. Fisher and F. Yates. 1938. Statistical tables for biological agricultural and medical research. Oliver and Boyd London 20 Example 12.  R. A. Fisher and F. Yates. 1938. Statistical tables for biological agricultural and medical research. 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Task and C. Clifton. 2013. What should we protect? Defining differential privacy for social network analysis. In Social Network Analysis and Mining.  C. Task and C. Clifton. 2013. What should we protect? Defining differential privacy for social network analysis. In Social Network Analysis and Mining.","DOI":"10.1109\/ASONAM.2012.73"},{"volume-title":"Nordic Workshop on Secure IT Systems (Nordsec).","author":"Toth G.","key":"e_1_2_1_21_1"},{"volume":"200","journal-title":"J. Pei.","author":"Wong R. 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In Cryptomathic."}],"container-title":["ACM Transactions on Internet Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3125622","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3125622","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3125622","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:30:06Z","timestamp":1750217406000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3125622"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,22]]},"references-count":34,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,5,31]]}},"alternative-id":["10.1145\/3125622"],"URL":"https:\/\/doi.org\/10.1145\/3125622","relation":{},"ISSN":["1533-5399","1557-6051"],"issn-type":[{"type":"print","value":"1533-5399"},{"type":"electronic","value":"1557-6051"}],"subject":[],"published":{"date-parts":[[2018,2,22]]},"assertion":[{"value":"2017-03-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-07-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-02-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}