Hesitant Fuzzy-Based Computational Technique for Evaluating Lightweight Authentication Mechanisms

The rapidly changing digitalization of the energy sector, fueled by smart grids, the Industrial Internet of Things (IIoT), Advanced Metering Infrastructure (AMI), and Supervisory Control and Data Acquisition (SCADA) systems, is leading to a great and symmetrical improvement in workflow and the ability to have real-time insights. In parallel, the massive adoption of low-power and resource-constrained devices that are still connected makes cybersecurity threats more serious and thus necessitates lightweight authentication mechanisms to have safe, secure, and symmetrical communicative. Selecting the right authentication method involves a challenging multi-criteria decision-making (MCDM) process where various factors such as security aspects, computation power needed, communication capabilities that can be delivered, and deployment-related aspects are considered together, along with inherent uncertainties in expert evaluations. This paper proposes a Hesitant Fuzzy (HF)-based hybrid method that combines the Analytic Network Process (ANP) with the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for the evaluation of lightweight authentication systems in the energy domain. This symmetrical HF-ANP is used for the modeling of the interrelations between major evaluation criteria such as security strength, computation efficiency, communication effectiveness, and deployment scalability. It can also handle the experts’ hesitant and uncertain preferences. The calculated weighting factors are then input to the HF-TOPSIS method to rank five different lightweight authentication protocols: Hash-Based Authentication, Elliptic Curve Cryptography (ECC)-Based Lightweight Authentication, Physical Unclonable Function (PUF)-Based Authentication, Blockchain-Assisted Lightweight Authentication, and Certificate-less Lightweight Authentication. Furthermore, sensitivity analysis and comparison analysis are conducted to verify the strength, symmetry, consistency, and reliability of the proposed framework. Our results indicate that the integrated HF-ANP and TOPSIS procedure provides a symmetrical, comprehensive, and systematic decision-making tool to appraise lightweight authentication techniques amid uncertainties. The proposed method will be very beneficial for different types of energy industrial players, system designers, and security experts to pick secure, efficient, and scalable methods of authentication to protect the critical energy facilities against the new generation of cyber threats.