{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T09:44:31Z","timestamp":1753868671073,"version":"3.41.2"},"reference-count":37,"publisher":"Wiley","issue":"19","license":[{"start":{"date-parts":[[2020,4,13]],"date-time":"2020-04-13T00:00:00Z","timestamp":1586736000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2020,10,10]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>Being part of public transportations, the bike sharing system plays an important role in solving the \u201clast mile\u201d problem. With more advantages than traditional bike sharing systems relying on fixed docks, dockless bike sharing systems are rapidly expanding, which generally operated under cloud\u2010based architectures. Emerging Things\u2010Edge\u2010Cloud (TEC) architectures are showing many advantages than cloud\u2010based architectures including greater potential in reducing risks of privacy leakage due to their decentralized computing manners. However, even in the TEC architecture, differential attacks, which aims to mine information of individuals in the aggregated data, still cause major threats. To solve this problem, this article proposes a novel encoding and decoding framework within the TEC architecture for time series predictions in bike sharing systems, with considerations of guaranteeing differential privacy. In particular, we first construct a dynamic autoencoder based on the Long Short Term Memory (LSTM) network, then the collected raw temporal data are encoded into a hidden state in the edge end. In the cloud end, the trained output weights are used to reconstruct the current time series and predict the next\u2010period time series according to received hidden states. This framework not only improves the computation efficiency of bike sharing system by leveraging computing power at the node end but also provides safer data publications that meet the differential privacy requirements. Experiments are conducted on real\u2010world datasets, results demonstrate the effectiveness of the proposed framework in providing data services with both high utility in sequence predictions and high safety level for users' privacy.<\/jats:p>","DOI":"10.1002\/cpe.5770","type":"journal-article","created":{"date-parts":[[2020,4,13]],"date-time":"2020-04-13T16:00:35Z","timestamp":1586793635000},"update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Guaranteeing differential privacy for sequence predictions in bike sharing systems"],"prefix":"10.1002","volume":"32","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-0652-0683","authenticated-orcid":false,"given":"Zhipu","family":"Xie","sequence":"first","affiliation":[{"name":"State Key Laboratory of Software Development Environment Beihang University  Beijing China"},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bowen","family":"Du","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Software Development Environment Beihang University  Beijing China"},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shangfo","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Software Development Environment Beihang University  Beijing China"},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Software Development Environment Beihang University  Beijing China"},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leilei","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Software Development Environment Beihang University  Beijing China"},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weifeng","family":"Lv","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Software Development Environment Beihang University  Beijing China"},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,4,13]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.14512\/gaia.22.4.5"},{"key":"e_1_2_7_3_1","first-page":"529","article-title":"The sharing economy and consumer protection regulation: the case for policy change","volume":"8","author":"Koopman C","year":"2014","journal-title":"J Bus Entrepreneurship L"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.5038\/2375-0901.12.4.3"},{"issue":"1","key":"e_1_2_7_5_1","first-page":"23","article-title":"The role of smart bike\u2010sharing systems in urban mobility","volume":"2","author":"Midgley P","year":"2009","journal-title":"Journeys"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1049\/cje.2016.11.016"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2018.1700169"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12599-015-0420-2"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.23552"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2778504"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2015.32"},{"key":"e_1_2_7_12_1","doi-asserted-by":"crossref","unstructured":"ChangH HariA MukherjeeS LakshmanT. 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