A formal model for blockchain-based consent management in data sharing
Consent is one of six legal bases for personal data processing mentioned in the General Data Protection Regulation (GDPR). The GDPR is a privacy law giving European Union (EU) citizens authority over personal data. It enforces software systems to collect, analyze, and share only necessary informatio...
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Published in | Journal of logical and algebraic methods in programming Vol. 134; p. 100886 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier Inc
01.08.2023
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Subjects | |
Online Access | Get full text |
ISSN | 2352-2208 |
DOI | 10.1016/j.jlamp.2023.100886 |
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Abstract | Consent is one of six legal bases for personal data processing mentioned in the General Data Protection Regulation (GDPR). The GDPR is a privacy law giving European Union (EU) citizens authority over personal data. It enforces software systems to collect, analyze, and share only necessary information (‘data minimization’) following the specific purpose (‘consent’). The GDPR defines consent as permission of individuals (‘data subjects’) to give organizations (‘data controllers’) processing their personal data. Without a data subject's consent, the data controller processes personal data unlawfully. Therefore, consent management is an essential component of a software system to build data subjects' trust and engagement. However, sharing data can lead to a potential loss of control over personal data, as data are across boundaries between software services. One of the significant risks is caused by a lack of developers' experience in data protection practices. Hence, in this paper, we propose to use blockchain technology to manage data subjects' informed consent for data sharing to build trust, transparency, and traceability to share data across software services. We formalized the semantics of smart contracts to extend the blockchain features to validate the consent authorization and manage the request-response interaction between the services. Furthermore, we used the Event-B method to describe the dynamic behavior of the proposed model and prove its correctness. Finally, we provided a mapping from the formal model to a smart contract class diagram and a prototype called SmartDataTrust implemented with solidity and Python REST API that developers can easily utilize. |
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AbstractList | Consent is one of six legal bases for personal data processing mentioned in the General Data Protection Regulation (GDPR). The GDPR is a privacy law giving European Union (EU) citizens authority over personal data. It enforces software systems to collect, analyze, and share only necessary information (‘data minimization’) following the specific purpose (‘consent’). The GDPR defines consent as permission of individuals (‘data subjects’) to give organizations (‘data controllers’) processing their personal data. Without a data subject's consent, the data controller processes personal data unlawfully. Therefore, consent management is an essential component of a software system to build data subjects' trust and engagement. However, sharing data can lead to a potential loss of control over personal data, as data are across boundaries between software services. One of the significant risks is caused by a lack of developers' experience in data protection practices. Hence, in this paper, we propose to use blockchain technology to manage data subjects' informed consent for data sharing to build trust, transparency, and traceability to share data across software services. We formalized the semantics of smart contracts to extend the blockchain features to validate the consent authorization and manage the request-response interaction between the services. Furthermore, we used the Event-B method to describe the dynamic behavior of the proposed model and prove its correctness. Finally, we provided a mapping from the formal model to a smart contract class diagram and a prototype called SmartDataTrust implemented with solidity and Python REST API that developers can easily utilize. |
ArticleNumber | 100886 |
Author | Peyrone, Neda Wichadakul, Duangdao |
Author_xml | – sequence: 1 givenname: Neda orcidid: 0000-0002-3659-4053 surname: Peyrone fullname: Peyrone, Neda email: peyrone.n@gmail.com organization: Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand – sequence: 2 givenname: Duangdao surname: Wichadakul fullname: Wichadakul, Duangdao email: duangdao.w@chula.ac.th organization: Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand |
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CitedBy_id | crossref_primary_10_1016_j_jnca_2023_103695 crossref_primary_10_2478_jec_2024_0028 |
Cites_doi | 10.3390/s21237994 10.1177/2043820613513388 10.1109/ACCESS.2022.3184726 10.1080/13600869.2013.801589 10.1007/s10009-010-0145-y 10.1007/s00779-021-01544-1 10.1038/s41431-019-0560-9 10.1007/s12083-021-01127-0 10.3390/healthcare9020137 10.1080/00207543.2022.2039413 10.1109/ACCESS.2020.3014565 10.1145/3434186 10.1088/1742-6596/1964/4/042005 10.1017/dap.2020.1 10.1007/s11280-021-00923-1 10.1088/1742-6596/1767/1/012056 10.3390/app112210574 10.22215/timreview/1325 10.1109/MCE.2019.2953739 10.1109/ACCESS.2019.2936094 |
ContentType | Journal Article |
Copyright | 2023 Elsevier Inc. |
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Keywords | Event-B Privacy by design Consent management Smart contracts Data protection GDPR |
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Snippet | Consent is one of six legal bases for personal data processing mentioned in the General Data Protection Regulation (GDPR). The GDPR is a privacy law giving... |
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