{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:54:39Z","timestamp":1772175279578,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T00:00:00Z","timestamp":1677801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2021YFB3101903"],"award-info":[{"award-number":["2021YFB3101903"]}]},{"name":"the National Key R&amp;D Program of China","award":["2022YFB3104900"],"award-info":[{"award-number":["2022YFB3104900"]}]},{"name":"the National Key R&amp;D Program of China","award":["2019YFB2102403"],"award-info":[{"award-number":["2019YFB2102403"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cryptography"],"abstract":"<jats:p>With the development of the mobile internet, service providers obtain data and resources through a large number of terminal user devices. They use private data for business empowerment, which improves the user experience while causing users\u2019 privacy disclosure. Current research ignores the impact of disclosing user non-sensitive attributes under a single scenario of data sharing and lacks consideration of users\u2019 privacy preferences. This paper constructs a data-sharing privacy metrics model based on information entropy and group privacy preferences. Use information theory to model the correlation of the privacy metrics problem, the improved entropy weight algorithm to measure the overall privacy of the data, and the analytic hierarchy process to correct user privacy preferences. Experiments show that this privacy metrics model can better quantify data privacy than conventional methods, provide a reliable evaluation mechanism for privacy security in data sharing and publishing scenarios, and help to enhance data privacy protection.<\/jats:p>","DOI":"10.3390\/cryptography7010011","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T01:35:30Z","timestamp":1678066530000},"page":"11","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Data Sharing Privacy Metrics Model Based on Information Entropy and Group Privacy Preference"],"prefix":"10.3390","volume":"7","author":[{"given":"Yihong","family":"Guo","sequence":"first","affiliation":[{"name":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China"},{"name":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinxin","family":"Zuo","sequence":"additional","affiliation":[{"name":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China"},{"name":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9392-0655","authenticated-orcid":false,"given":"Ziyu","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China"},{"name":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China"},{"name":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueming","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China"},{"name":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ouaftouh, S., Zellou, A., and Idri, A. (2015, January 17). User Profile Model: A User Dimension Based Classification. Proceedings of the 10th International Conference on Intelligent Systems: Theories and Applications (SITA), Taipei, China.","DOI":"10.1109\/SITA.2015.7358378"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MCOM.2011.6069707","article-title":"Mobile crowdsensing: Current state and future challenges","volume":"49","author":"Ganti","year":"2011","journal-title":"IEEE Commun. Mag."},{"key":"ref_3","first-page":"246","article-title":"Big data security and privacy protection","volume":"37","author":"Feng","year":"2014","journal-title":"Chin. J. Comput."},{"key":"ref_4","first-page":"83","article-title":"Decision making with the analytic hierarchy process","volume":"1","author":"Saaty","year":"2008","journal-title":"Int. J. Serv. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1020","DOI":"10.1016\/S1001-0742(06)60032-6","article-title":"Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment","volume":"18","author":"Zou","year":"2006","journal-title":"J. Environ. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"847","DOI":"10.3724\/SP.J.1016.2009.00847","article-title":"Privacy preservation in database applications: A survey","volume":"32","author":"Zhou","year":"2009","journal-title":"Chin. J. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1142\/S0218488502001648","article-title":"K-Anonymity: A model for protecting privacy","volume":"10","author":"Sweeney","year":"2002","journal-title":"Int. J. Uncertain. Fuzziness Knowl.-Based Syst."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Machanavajjhala, A., Kifer, D., Gehrke, J., and Venkitasubramaniam, M. (2006, January 3). L-Diversity: Privacy Beyond K-Anonymity. Proceedings of the 22nd International Conference on Data Engineering (ICDE), Atlanta, GA, USA.","DOI":"10.1109\/ICDE.2006.1"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Li, N., Li, T., and Venkatasubramanian, S. (2007, January 14). T-Closeness: Privacy beyond k-Anonymity and l-Diversity. Proceedings of the 23rd International Conference on Data Engineering (ICDE), Istanbul, Turkey.","DOI":"10.1109\/ICDE.2007.367856"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zang, H., and Bolot, J. (2011, January 9). Anonymization of Location Data Does Not Work: A Large-Scale Measurement Study. Proceedings of the 17th Annual International Conference on Mobile Computing and Networking, MOBICOM 2011, Las Vegas, NV, USA.","DOI":"10.1145\/2030613.2030630"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/11681878_14","article-title":"Calibrating noise to sensitivity in private data analysis","volume":"3876","author":"Dwork","year":"2006","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1561\/0400000042","article-title":"The Algorithmic Foundations of Differential Privacy","volume":"9","author":"Dwork","year":"2013","journal-title":"Found. Trends Theor. Comput. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Qu, L., Yang, J., Yan, X., Ma, L., Yang, Q., and Han, Y. (2021, January 6\u201310). Research on Privacy Protection Technology for Data Publishing. Proceedings of the 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C), Hainan, China.","DOI":"10.1109\/QRS-C55045.2021.00151"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1109\/TKDE.2018.2797092","article-title":"Privacy Characterization and Quantification in Data Publishing","volume":"30","author":"Afifi","year":"2018","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.knosys.2018.08.017","article-title":"Restricted Sensitive Attributes-based Sequential Anonymization (RSA-SA) approach for privacy-preserving data stream publishing","volume":"164","author":"Abdelhameed","year":"2019","journal-title":"Knowl.-Based Syst."},{"key":"ref_16","first-page":"2506","article-title":"General Confidentiality and Utility Metrics for Privacy-Preserving Data Publishing Based on the Permutation Model","volume":"18","author":"Muralidhar","year":"2021","journal-title":"IEEE Trans. Dependable Secur. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"89555","DOI":"10.1109\/ACCESS.2022.3201641","article-title":"A Targeted Privacy-Preserving Data Publishing Method Based on Bayesian Network","volume":"10","author":"Zhou","year":"2022","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"D\u0131az, C., Seys, S., Claessens, J., and Preneel, B. (2002, January 14). Towards Measuring Anonymity. Proceedings of the 2nd International Workshop on Privacy-Enhancing Technologies, San Francisco, CA, USA.","DOI":"10.1007\/3-540-36467-6_5"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Gao, F., He, J., Peng, S., and Wu, X. (2010, January 4). A Quantifying Metric for Privacy Protection Based on Information Theory. Proceedings of the 3rd International Symposium on Intelligent Information Technology and Security Informatics, Jinggangshan, China.","DOI":"10.1109\/IITSI.2010.107"},{"key":"ref_20","first-page":"1891","article-title":"Information entropy models and privacy metrics methods for privacy protection","volume":"27","author":"Peng","year":"2016","journal-title":"J. Softw."},{"key":"ref_21","first-page":"130","article-title":"Privacy protection model and privacy metric methods based on privacy preference","volume":"45","author":"Zhang","year":"2018","journal-title":"Comput. Sci."},{"key":"ref_22","first-page":"270","article-title":"Privacy metric model of differential privacy via graph theory and mutual information","volume":"47","author":"Wang","year":"2020","journal-title":"Comput. Sci."},{"key":"ref_23","first-page":"10","article-title":"Metric and classification model for privacy data based on Shannon information entropy and BP neural network","volume":"39","author":"Yu","year":"2018","journal-title":"J. Commun."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Arca, S., and Hewett, R. (2020, January 16). Is Entropy Enough for Measuring Privacy?. Proceedings of the 2020 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA,.","DOI":"10.1109\/CSCI51800.2020.00249"},{"key":"ref_25","first-page":"157","article-title":"Dynamic privacy measurement model and evaluation system for mobile edge crowdsensing","volume":"7","author":"Zhao","year":"2021","journal-title":"Chin. J. Netw. Inf. Secur."},{"key":"ref_26","unstructured":"Kohavi, R., Becker, B., and University of California (2022, July 25). Adult Data Set. UCI Machine Learning Repository. Available online: https:\/\/archive.ics.uci.edu\/ml\/datasets\/Adult."}],"container-title":["Cryptography"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2410-387X\/7\/1\/11\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:47:25Z","timestamp":1760122045000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2410-387X\/7\/1\/11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,3]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["cryptography7010011"],"URL":"https:\/\/doi.org\/10.3390\/cryptography7010011","relation":{},"ISSN":["2410-387X"],"issn-type":[{"value":"2410-387X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,3]]}}}