{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T09:12:56Z","timestamp":1774084376893,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,28]],"date-time":"2021-08-28T00:00:00Z","timestamp":1630108800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005856","name":"Faculdade de Ci\u00eancias e Tecnologia, Universidade Nova de Lisboa","doi-asserted-by":"publisher","award":["PD\/BD\/128149\/2016"],"award-info":[{"award-number":["PD\/BD\/128149\/2016"]}],"id":[{"id":"10.13039\/501100005856","id-type":"DOI","asserted-by":"publisher"}]},{"name":"H2020-SUICT-03-2018","award":["830929"],"award-info":[{"award-number":["830929"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The growing demand for everyday data insights drives the pursuit of more sophisticated infrastructures and artificial intelligence algorithms. When combined with the growing number of interconnected devices, this originates concerns about scalability and privacy. The main problem is that devices can detect the environment and generate large volumes of possibly identifiable data. Public cloud-based technologies have been proposed as a solution, due to their high availability and low entry costs. However, there are growing concerns regarding data privacy, especially with the introduction of the new General Data Protection Regulation, due to the inherent lack of control caused by using off-premise computational resources on which public cloud belongs. Users have no control over the data uploaded to such services as the cloud, which increases the uncontrolled distribution of information to third parties. This work aims to provide a modular approach that uses cloud-of-clouds to store persistent data and reduce upfront costs while allowing information to remain private and under users\u2019 control. In addition to storage, this work also extends focus on usability modules that enable data sharing. Any user can securely share and analyze\/compute the uploaded data using private computing without revealing private data. This private computation can be training machine learning (ML) models. To achieve this, we use a combination of state-of-the-art technologies, such as MultiParty Computation (MPC) and K-anonymization to produce a complete system with intrinsic privacy properties.<\/jats:p>","DOI":"10.3390\/s21175805","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T22:58:15Z","timestamp":1630450695000},"page":"5805","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Towards a Modular On-Premise Approach for Data Sharing"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0125-4240","authenticated-orcid":false,"given":"Jo\u00e3o S.","family":"Resende","sequence":"first","affiliation":[{"name":"Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC-TEC), R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9794-227X","authenticated-orcid":false,"given":"Lu\u00eds","family":"Magalh\u00e3es","sequence":"additional","affiliation":[{"name":"Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"}]},{"given":"Andr\u00e9","family":"Brand\u00e3o","sequence":"additional","affiliation":[{"name":"Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1838-1417","authenticated-orcid":false,"given":"Rolando","family":"Martins","sequence":"additional","affiliation":[{"name":"Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC-TEC), R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"given":"Lu\u00eds","family":"Antunes","sequence":"additional","affiliation":[{"name":"Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2763","DOI":"10.1007\/s11227-016-1953-y","article-title":"Privacy in cloud computing environments: A survey and research challenges","volume":"73","author":"Ghorbel","year":"2017","journal-title":"J. Supercomput."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Chen, D., and Zhao, H. (2012, January 23\u201325). Data security and privacy protection issues in cloud computing. 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