Policy Conflict Resolution in IoT via Planning

Göynügür, Emre; Bernardini, Sara; Mel, Geeth de; Talamadupula, Kartik; Şensoy, Murat

doi:10.1007/978-3-319-57351-9_22

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…For example, the authors of [58] presented a game theory model for mutual intrusion detection in IoT, aiding nodes in decisionmaking. Similarly, [59] introduced a conflict resolution scheme for IoT services, using a semantic policy structure and soft constraints to address multi-service disputes.…”

Section: Security Requirements Researchmentioning

confidence: 99%

A Survey on Security, Privacy, Trust, and Architectural Challenges in IoT Systems

Adam,

Hammoudeh,

Alrawashdeh

et al. 2024

IEEE Access

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The Internet of Things (IoT) emerged as a pervasive technology, facilitating the seamless interaction of devices, individuals, and services, enabling data exchange and task execution across various domains. While the impact of IoT is undeniably transformative, its extensive proliferation raised significant concerns surrounding security, privacy, and trust, which stand as critical barriers to the widespread adoption and advancement of IoT technology. This review article explores IoT security, privacy, and trust research using a 3-layer IoT architecture. After introducing the fundamental tenets of IoT security, privacy, and trust, it proceeds to examine the prevalent security requirements within IoT architectures and their associated challenges. Then, the survey investigates the recent trends in research dedicated to addressing security, privacy, and trust issues within IoT systems. Furthermore, this article reviews the latest advancements and methodologies designed to secure IoT systems against security breaches and protect the privacy of sensitive data. Finally, the survey outlines unresolved challenges within the IoT security landscape and potential solutions. By offering this consolidated insight, this article offers a bridge between foundational and advanced IoT security topics, providing researchers with an in-depth understanding of current IoT security, privacy, and trust challenges, as well as cutting-edge solutions tailored to address the security and trust-related obstacles faced by IoT applications. This comprehensive overview equips the IoT community with the knowledge necessary to navigate the complex terrain of security, privacy, and trust in IoT systems.

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Section: Security Requirements Researchmentioning

confidence: 99%

A Survey on Security, Privacy, Trust, and Architectural Challenges in IoT Systems

Adam,

Hammoudeh,

Alrawashdeh

et al. 2024

IEEE Access

View full text Add to dashboard Cite

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“…In [ 104 ], the authors represent a scheme for resolving disputes between IoT-based services by redefining conflict resolution as a planning problem. They establish a semantic policy structure for IoT-based conflict identification and allow soft constraints to settle conflicts resulting from multiple services.…”

Section: Taxonomy Of Ml-based Aa For Iotmentioning

confidence: 99%

Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction

Ahmed

Tahir

Habaebi

et al. 2021

Sensors

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With the ongoing efforts for widespread Internet of Things (IoT) adoption, one of the key factors hindering the wide acceptance of IoT is security. Securing IoT networks such as the electric power grid or water supply systems has emerged as a major national and global priority. To address the security issue of IoT, several studies are being carried out that involve the use of, but are not limited to, blockchain, artificial intelligence, and edge/fog computing. Authentication and authorization are crucial aspects of the CIA triad to protect the network from malicious parties. However, existing authorization and authentication schemes are not sufficient for handling security, due to the scale of the IoT networks and the resource-constrained nature of devices. In order to overcome challenges due to various constraints of IoT networks, there is a significant interest in using machine learning techniques to assist in the authentication and authorization process for IoT. In this paper, recent advances in authentication and authorization techniques for IoT networks are reviewed. Based on the review, we present a taxonomy of authentication and authorization schemes in IoT focusing on machine learning-based schemes. Using the presented taxonomy, a thorough analysis is provided of the authentication and authorization (AA) security threats and challenges for IoT. Furthermore, various criteria to achieve a high degree of AA resiliency in IoT implementations to enhance IoT security are evaluated. Lastly, a detailed discussion on open issues, challenges, and future research directions is presented for enabling secure communication among IoT nodes.

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