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Authors: Luiz Lento 1 ; 2 ; Pedro Patinho 1 and Salvador Abreu 1 ; 2

Affiliations: 1 Department of Informatics, University of Évora, Portugal ; 2 NOVA-LINCS, University of Évora, Portugal

Keyword(s): Risk Management, IoT, Threat Mitigation, Probabilistic Logic, Fuzzy Logic.

Abstract: As the world becomes more and more dynamic and competitive, people live more and more connected, breathing a cybernetic reality in their lives. IoT systems also do not escape this reality, they are omnipresent, providing a wide range of services to their users, and increasing their quality of life, enabled by IoT devices. In parallel with this technology, information security problems are also part of this IoT evolution. A key issue with IoT environments is ensuring security across all services and devices. The diversity of threats, together with the lack of concern of most of its administrators and device designers, make the IoT network environment vulnerable. This article presents RTRMM, a logic-based security risk management model that can help protect IoT environments, with new strategies to detect, analyze and assess risks, making it possible to predict risks and aiming to manage them in real time, thereby improving the reliability and safety of the IoT environment. It makes use of a combination of probability, fuzzy logic, Markov Chains, Games Theory, and Logic Programming to specify, test and validate its functionalities. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Lento, L., Patinho, P. and Abreu, S. (2024). A Logic-Based Model to Reduce IoT Security Risks. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 1197-1204. DOI: 10.5220/0012455200003636

@conference{icaart24,
author={Luiz Lento and Pedro Patinho and Salvador Abreu},
title={A Logic-Based Model to Reduce IoT Security Risks},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={1197-1204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012455200003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - A Logic-Based Model to Reduce IoT Security Risks
SN - 978-989-758-680-4
IS - 2184-433X
AU - Lento, L.
AU - Patinho, P.
AU - Abreu, S.
PY - 2024
SP - 1197
EP - 1204
DO - 10.5220/0012455200003636
PB - SciTePress