A Normative Multiagent Approach to Represent Data Regulation Concerns

Paulo Henrique Alves, Fernando Correia, Isabella Frajhof, Clarisse Sieckenius de Souza, Helio Lopes

2023

Abstract

Data protection regulation is crucial to establishing the appropriate conduct in sharing and maintaining personal data. It aims to protect the Data Subjects’ data, and to define Data Controllers’ and Processors’ obligations. However, modeling systems to represent and comply with those regulations can be challenging. In this sense, Multiagent System (MAS) presents an opportunity to overcome this challenge. MAS is an artificial intelligence approach that enables the simulation of independent software agents considering environmental variables. Thus, combining data regulation directives and Normative MAS (NMAS) can allow the development of systems among distinct data regulation jurisdictions properly. This work proposes the DR-NMAS (Data Regulation by NMAS) employing Adaptative Normative Agent - Modeling Language (ANA-ML) and a Normative Agent Java Simulation (JSAN) extension to address data regulation concerns in an NMAS. As a result, we present a use case scenario in the Open Banking domain to employ the proposed extensions. Finally, this work concludes that NMAS can represent data regulation modeling and its application.

Paper Citation

in Harvard Style

Henrique Alves P., Correia F., Frajhof I., Sieckenius de Souza C. and Lopes H. (2023). A Normative Multiagent Approach to Represent Data Regulation Concerns. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-623-1, pages 330-337. DOI: 10.5220/0011750900003393

in Bibtex Style

@conference{icaart23,
author={Paulo Henrique Alves and Fernando Correia and Isabella Frajhof and Clarisse Sieckenius de Souza and Helio Lopes},
title={A Normative Multiagent Approach to Represent Data Regulation Concerns},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2023},
pages={330-337},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011750900003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - A Normative Multiagent Approach to Represent Data Regulation Concerns
SN - 978-989-758-623-1
AU - Henrique Alves P.
AU - Correia F.
AU - Frajhof I.
AU - Sieckenius de Souza C.
AU - Lopes H.
PY - 2023
SP - 330
EP - 337
DO - 10.5220/0011750900003393