TY - GEN
T1 - i-Right
T2 - 25th International Conference on Web Information Systems Engineering, WISE 2024
AU - Kounoudes, Alexia Dini
AU - Kapitsaki, Georgia M.
AU - Katakis, Ioannis
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Regulations and laws, such as the EU GDPR, require service providers to inform the users about their data collection and processing practices. The existing method used for the portrayal of the rights and responsibilities of both the user and the service provider in terms of data collection, processing and sharing, are the privacy policies, that depict the practices that an organization or company follows when handling the personal data of its users. In this work, we introduce an automated approach, i-Right that classifies the text of privacy policies from the domains of fitness trackers and smart homes, extracting information regarding the eight GDPR user rights present (e.g. Right to Object). Our results show that i-Right achieves classification of the text with high accuracy. The proposed approach could provide a valuable tool for users to understand how their personal data is handled by service providers and to comprehend the possible risks from using their devices. A side contribution of our work is the creation of a labelled dataset of 133 privacy policies to assist the above process.
AB - Regulations and laws, such as the EU GDPR, require service providers to inform the users about their data collection and processing practices. The existing method used for the portrayal of the rights and responsibilities of both the user and the service provider in terms of data collection, processing and sharing, are the privacy policies, that depict the practices that an organization or company follows when handling the personal data of its users. In this work, we introduce an automated approach, i-Right that classifies the text of privacy policies from the domains of fitness trackers and smart homes, extracting information regarding the eight GDPR user rights present (e.g. Right to Object). Our results show that i-Right achieves classification of the text with high accuracy. The proposed approach could provide a valuable tool for users to understand how their personal data is handled by service providers and to comprehend the possible risks from using their devices. A side contribution of our work is the creation of a labelled dataset of 133 privacy policies to assist the above process.
KW - GDPR
KW - privacy policy
KW - privacy protection
KW - smart home
UR - http://www.scopus.com/inward/record.url?scp=85211230743&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-0576-7_19
DO - 10.1007/978-981-96-0576-7_19
M3 - Conference contribution
AN - SCOPUS:85211230743
SN - 9789819605750
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 254
BT - Web Information Systems Engineering – WISE 2024 - 25th International Conference, Proceedings
A2 - Barhamgi, Mahmoud
A2 - Wang, Hua
A2 - Wang, Xin
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 2 December 2024 through 5 December 2024
ER -