Intelligent Hybrid Selection of Secure and Energy-Efficient Lightweight Encryption Algorithms for Sustainable Internet of Things

Mian Muhammad Akhtar Hayat; Majid Khan

doi:10.31181/sems41202697

Authors

Mian Muhammad Akhtar Hayat Department of Applied Mathematics & Statistics, Institute of Space Technology, Islamabad, Pakistan Author https://orcid.org/0009-0004-8159-1072
Majid Khan Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia Author https://orcid.org/0000-0001-5454-3770

DOI:

https://doi.org/10.31181/sems41202697

Keywords:

Lightweight Cryptography, Internet of Things, Resource-Constrained Devices, Energy-Efficient Computing, Low-Power Internet of Things, Resource Efficiency, Sustainable Digital Infrastructure, Information Confidentiality, Multi-Criteria Decision-Making, CRITIC, CODAS, TOPSIS

Abstract

The rapid growth of Internet of Things (IoT) devices has increased the demand for secure and resource-efficient confidentiality mechanisms in constrained environments. Selecting an appropriate lightweight cipher is challenging because its implementation involves trade-offs among hardware resources, computational performance, memory, and energy requirements. This study presents an objective multi-criteria framework for evaluating well-established lightweight encryption algorithms using eight implementation-critical criteria: chip area, throughput, energy consumption, power consumption, latency, algorithm size, RAM size, and key size. The criteria importance through inter-criteria correlation (CRITIC) method is employed to determine objective criterion weights, while multiplicative exponential weighting (MEW), combinative distance-based assessment (CODAS), and technique for order preference by similarity to ideal solution (TOPSIS) are used for comparative ranking. The proposed CRITIC multi-criteria framework enables systematic selection of lightweight ciphers by jointly considering computational, hardware, memory, and energy efficiency. By promoting low-power operation and efficient utilization of computational resources, the framework may contribute to more sustainable and resilient IoT infrastructures.

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