TY - GEN
T1 - CompAi
T2 - 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
AU - Cejas, Orlando Amaral
AU - Abualhaija, Sallam
AU - Briand, Lionel C.
N1 - Publisher Copyright:
© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/10/27
Y1 - 2024/10/27
N2 - We introduce CompAl - a tool for checking the completeness of privacy policies against the general data protection regulation (GDPR). CompAl 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, CompAl 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, CompAl can determine the potential incompleteness violations in the input policy with an accuracy of ≈96%. CompAl generates a detailed report that can be easily reviewed and validated by experts. The source code of CompAl 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.
AB - We introduce CompAl - a tool for checking the completeness of privacy policies against the general data protection regulation (GDPR). CompAl 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, CompAl 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, CompAl can determine the potential incompleteness violations in the input policy with an accuracy of ≈96%. CompAl generates a detailed report that can be easily reviewed and validated by experts. The source code of CompAl 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.
KW - artificial intelligence (AI)
KW - machine learning (ML)
KW - natural language processing (NLP)
KW - privacy
KW - regulatory compliance
KW - requirements engineering (RE)
KW - the general data protection regulation (GDPR)
UR - http://www.scopus.com/inward/record.url?scp=85212426022&partnerID=8YFLogxK
U2 - 10.1145/3691620.3695353
DO - 10.1145/3691620.3695353
M3 - Conference contribution
AN - SCOPUS:85212426022
T3 - Proceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
SP - 2366
EP - 2369
BT - Proceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
PB - Association for Computing Machinery, Inc
Y2 - 28 October 2024 through 1 November 2024
ER -