{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T07:08:35Z","timestamp":1723619315121},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684482","type":"print"},{"value":"9781643684499","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T00:00:00Z","timestamp":1697673600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,19]]},"abstract":"<jats:p>In today\u2019s networked systems a massive amount of data is produced every day. These data can be modelled using graphs, where the nodes typically correspond to users or devices and the edges to the connections between them. Almost all networks change over time, with new nodes and edges appearing or disappearing as the system matures. Therefore dynamic graph models are more adequate to analyse such networks than static graphs, and appropriate tools need to be implemented to protect them. In this paper we obtain an edge differentially private version of dynamic stochastic block model. We show experimentally that the trends in the dynamic stochastic block model obtained from the original data are well preserved with the additional privacy guarantees.<\/jats:p>","DOI":"10.3233\/faia230693","type":"book-chapter","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T08:15:03Z","timestamp":1698048903000},"source":"Crossref","is-referenced-by-count":1,"title":["Adding Edge Local Differential Privacy to the Dynamic Stochastic Block Model"],"prefix":"10.3233","author":[{"given":"Sudipta","family":"Paul","sequence":"first","affiliation":[{"name":"Department of Computing Science, Ume\u00e5 Universitet, Umea, Sweden"}]},{"given":"Juli\u00e1n","family":"Salas","sequence":"additional","affiliation":[{"name":"Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Barcelona, Spain"}]},{"given":"Vicen\u00e7","family":"Torra","sequence":"additional","affiliation":[{"name":"Department of Computing Science, Ume\u00e5 Universitet, Umea, Sweden"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Artificial Intelligence Research and Development"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230693","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T08:15:04Z","timestamp":1698048904000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230693"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,19]]},"ISBN":["9781643684482","9781643684499"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230693","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,19]]}}}