journal article·2023-01-20Open access

Towards a Provably Secure Authentication Protocol for Fog-Driven IoT-Based Systems

Minahil Rana, Khalid Mahmood, Muhammad Asad Saleem, Fadi Al-Turjman, Manjur Sayyadbadasha Kolhar, Chadi Altrjman

Applied Sciences· Volume 13· Issue 3

Abstract

The emergence of fog-based Internet of Things (IoT) systems have played a significant role in enhancing the applicability of the IoT paradigm. In such systems, fog-nodes are proficient enough to retain, process and transmit the data coming from IoT devices. Nevertheless, as an extension of cloud computing, inheriting the security and privacy concerns of cloud computing is also inevitable in fog-based IoT systems. To deal with such challenges, a diverse range of security solutions are reported in the literature. However, most of them have several limitations (i.e., vulnerability to known security attacks and high computation overhead) that curtail their practical implementation applicability. Keeping these limitations in mind, this paper propose a privacy-preserving hash-based authenticated key agreement protocol using XOR and concatenation operations for fog-driven IoT systems. Using healthcare as a case study, the security of the novel protocol is evaluated by using informal and formal security analysis. In order to obtain the experimental results, the key cryptographic operations used at the user, fog node and cloud server-side are implemented on a mobile device, Arduino and cloud server, respectively. Findings from the performance evaluation results show that the proposed protocol has the least computation cost compared to several related competing protocols.
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Research context

OpenAlex topics: Advanced Authentication Protocols Security · User Authentication and Security Systems · IoT and Edge/Fog Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science, COMSATS University Islamabad, Sahiwal Campus, Sahiwal 57000, Pakistan

Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan

Department of Computer Science, University of Sahiwal, Sahiwal 57000, Pakistan

Research Center for AI and IoT, Artificial Intelligence Engineering Deptartment, Near East University, Mersin 10, Turkey

Deptartment Computer Science, College of Arts and Science, Prince Sattam Bin Abdulaziz University, Al-Kharj 11990, Saudi Arabia

Research Center for AI and IoT, Faculty of Engineering, University of Kyrenia, Kyrenia, Mersin 10, Turkey

Faculty of Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada

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