Analyzing GDPR compliance in Cloud Services' privacy policies using Textual Fuzzy Interpretive Structural Modeling (TFISM)
| dc.contributor.author | Razavisousan, Ronak | |
| dc.contributor.author | Joshi, Karuna | |
| dc.date.accessioned | 2021-08-06T18:12:25Z | |
| dc.date.available | 2021-08-06T18:12:25Z | |
| dc.date.issued | 2021-09-06 | |
| dc.description | IEEE International Services Computing Conference (SCC) 2021 in IEEE World Congress on Services 2021 | en_US |
| dc.description.abstract | Cloud Service providers must comply with data protection regulations, like European Union (EU) General Data Protection Regulation (GDPR), to ensure their users' personal data security and privacy. Hence, the service privacy policies and terms of service documents refer to the rules it complies with within the data protection regulation. However, these documents contain legalese jargon that requires significant manual effort to parse and confirm compliance. We have developed a novel methodology, Textual Fuzzy Interpretive Structural Modeling (TFISM), that automatically analyzes large textual datasets to identify driving and dependent factors in the dataset. TFISM enhances Interpretive Structural Modeling (ISM) to analyze textual data and integrate it with Artificial Intelligence and Text extraction techniques. Using TFISM, we identified the critical factors in GDPR and compared them with various Cloud Service privacy policies. In this paper, we present the results of this study that identified how different factors are emphasized in GDPR and 224 publicly available service privacy policies. TFISM can be used both by service providers and consumers to automatically analyze how close a service privacy policy aligns with the GDPR. | en_US |
| dc.description.sponsorship | This research was partially supported by a DoD supplement to the NSF award 1747724, Phase I IUCRC UMBC: Center for Accelerated Real-time Analytics (CARTA). We also thank Mrs. Lavanya Elluri for her professional consultation to select the list of variables and analyzing the results. | en_US |
| dc.description.uri | https://ieeexplore.ieee.org/document/9592430 | en_US |
| dc.format.extent | 10 pages | en_US |
| dc.genre | conference papers and proceedings | en_US |
| dc.genre | preprints | en_US |
| dc.identifier | doi:10.13016/m2byjg-ks5a | |
| dc.identifier.citation | R. Razavisousan and K. P. Joshi, "Analyzing GDPR compliance in Cloud Services' privacy policies using Textual Fuzzy Interpretive Structural Modeling (TFISM)," 2021 IEEE International Conference on Services Computing (SCC), 2021, pp. 89-98, doi: 10.1109/SCC53864.2021.00021. | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/22330 | |
| dc.identifier.uri | https://doi.org/10.1109/SCC53864.2021.00021 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | 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 Student Collection | |
| dc.rights | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
| dc.subject | UMBC Ebiquity Research Group | en_US |
| dc.title | Analyzing GDPR compliance in Cloud Services' privacy policies using Textual Fuzzy Interpretive Structural Modeling (TFISM) | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0002-6354-1686 | en_US |