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A Mechanism for Securing IoT-enabled Applications at the Fog Layer

Abbas, N, Asim, M, Tariq, N, Baker, T and Abbas, S (2019) A Mechanism for Securing IoT-enabled Applications at the Fog Layer. Journal of Sensor and Actuator Networks (JSAN), 8 (1). ISSN 2224-2708

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The Internet of Things (IoT) is an emerging paradigm branded by heterogeneous technologies composed of smart ubiquitous objects that are seamlessly connected to the Internet. These objects are deployed as Low power and Lossy Networks (LLN) to provide innovative services in various application domains, such as smart cities, smart health, smart communities. The LLN is a form of a network where the interconnected devices are highly resource-constrained (i.e., power, memory, and processing) and characterized by high loss rates, low data rates and instability in the communication links. Additionally, IoT devices produce a massive amount of confidential and security-sensitive data. Various cryptographic-based techniques exist that can effectively cope with security attacks, but are not suitable for IoT as they incur high consumption of resources (i.e., memory, storage and processing). One way to address this problem is by offloading the additional security-related operations to a more resourceful entity such as a fog-based node. Generally, fog computing enables security and analysis of latency-sensitive data directly at the network’s edge. This paper proposes a novel Fog Security Service (FSS) to provide end-to-end security at fog layer for IoT devices, using two well-established cryptographic schemes, identity-based encryption and identity-based signature. The FSS provides security services, such as authentication, confidentiality, and non-repudiation. The proposed architecture is implemented and evaluated in OPNET simulator using a single network topology with different traffic loads. The FSS performed better when compared with the APaaS and the legacy method.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: MDPI
Date Deposited: 14 Feb 2019 10:43
Last Modified: 04 Sep 2021 09:43
DOI or ID number: 10.3390/jsan8010016
URI: https://researchonline.ljmu.ac.uk/id/eprint/10162
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