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CompAi: A Tool for GDPR completeness checking of privacy policies using artificial intelligence

Date
2024
Abstract
We introduce๐ถ๐‘œ๐‘š๐‘๐ด๐œ„ โ€“ a tool for checking the completeness of privacy policies against the general data protection regulation (GDPR). ๐ถ๐‘œ๐‘š๐‘๐ด๐œ„ facilitates the analysis of privacy policies to check their compliance to GDPR requirements. Since privacy policies serve as an agreement between a software system and its prospective users, the policy must fully capture such requirements to ensure that collected personal data of individuals (or users) remains protected as specified by the GDPR. For a given privacy policy, ๐ถ๐‘œ๐‘š๐‘๐ด๐œ„ semantically analyzes its textual content against a comprehensive conceptual model which captures all information types that might appear in any policy. Based on this analysis, alongside some input from the end user, ๐ถ๐‘œ๐‘š๐‘๐ด๐œ„ can determine the potential incompleteness violations in the input policy with an accuracy of โ‰ˆ96%. ๐ถ๐‘œ๐‘š๐‘๐ด๐œ„ generates a detailed report that can be easily reviewed and validated by experts. The source code of๐ถ๐‘œ๐‘š๐‘๐ด๐œ„ is publicly available on https: //figshare.com/articles/online_resource/CompAI/23676069, and a demo of the tool is available on https://youtu.be/zwa_tM3fXHU.
Supervisor
Description
Publisher
Association for Computing Machinery
Citation
ASE '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering pp. 2366 - 2369
Collections
Lero - The Science Foundation Ireland Research Centre for Software
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Briand_2024_CompiAi.pdf
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Keywords
requirements engineering (RE), regulatory compliance, privacy, the General Data Protection Regulation (GDPR), Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning (ML), Software engineering
ULRR Identifiers
https://doi.org/10.34961/researchrepository-ul.28436630
 https://researchrepository.ul.ie/handle/10344/14367
Funding code
Funding Information
This research was supported by Linklaters and Luxembourgโ€™s National Research Fund (FNR) in whole, or in part, under grant references BRIDGES/19/IS/13759068/ARTAGO and NCER22/IS/16570468/NCER-FT. Lionel Briand was partly supported by the DG and CRC programmes of NSERC Canada. For the purpose of open access, and in fulfillment of the obligations arising from the grant agreement, the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission.
Sustainable Development Goals
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Meetings and Proceedings
Rights
https://creativecommons.org/licenses/by-nc-sa/4.0/
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