Automating Privacy Compliance Using Policy Integrated Blockchain
dc.contributor.author | Joshi, Karuna Pande | |
dc.contributor.author | Banerjee, Agniva | |
dc.date.accessioned | 2019-02-27T15:46:04Z | |
dc.date.available | 2019-02-27T15:46:04Z | |
dc.date.issued | 2019-02-05 | |
dc.description.abstract | An essential requirement of any information management system is to protect data and resources against breach or improper modifications, while at the same time ensuring data access to legitimate users. Systems handling personal data are mandated to track its flow to comply with data protection regulations. We have built a novel framework that integrates semantically rich data privacy knowledge graph with Hyperledger Fabric blockchain technology, to develop an automated access-control and audit mechanism that enforces users’ data privacy policies while sharing their data with third parties. Our blockchain based data-sharing solution addresses two of the most critical challenges: transaction verification and permissioned data obfuscation. Our solution ensures accountability for data sharing in the cloud by incorporating a secure and efficient system for End-to-End provenance. In this paper, we describe this framework along with the comprehensive semantically rich knowledge graph that we have developed to capture rules embedded in data privacy policy documents. Our framework can be used by organizations to automate compliance of their Cloud datasets. | en_US |
dc.description.sponsorship | This research was partially supported by a DoD supplement to the NSF award #1439663: NSF I/UCRC Center for Hybrid Multicore Productivity Research (CHMPR). | en_US |
dc.description.uri | https://www.mdpi.com/2410-387X/3/1/7 | en_US |
dc.format.extent | 22 pages | en_US |
dc.genre | journal articles | en_US |
dc.identifier | doi:10.13016/m2vrgk-5s0u | |
dc.identifier.citation | Karuna Pande Joshi, Agniva Banerjee, Automating Privacy Compliance Using Policy Integrated Blockchain, Cryptography 2019, 3(1), 7, https://doi.org/10.3390/cryptography3010007 | en_US |
dc.identifier.uri | https://doi.org/10.3390/cryptography3010007 | |
dc.identifier.uri | http://hdl.handle.net/11603/12881 | |
dc.language.iso | en_US | en_US |
dc.publisher | MDPI | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Information Systems Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
dc.rights | Attribution 4.0 International (CC BY 4.0) | * |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | blockchain | en_US |
dc.subject | big data | en_US |
dc.subject | semantic web | en_US |
dc.subject | privacy policy | en_US |
dc.subject | ontology | en_US |
dc.subject | knowledge graph | en_US |
dc.subject | data compliance | en_US |
dc.subject | UMBC Ebiquity Research Group | |
dc.title | Automating Privacy Compliance Using Policy Integrated Blockchain | en_US |
dc.type | Text | en_US |