journal article·2024Open access

Enhancing IoT Security: Quantum-Level Resilience against Threats

Hosam Alhakami

Computers, Materials & Continua· Volume 78· Issue 1

Abstract

The rapid growth of the Internet of Things (IoT) operations has necessitated the incorporation of quantum computing technologies to meet its expanding needs. This integration is motivated by the need to solve the specific issues provided by the expansion of IoT and the potential benefits that quantum computing can offer in this scenario. The combination of IoT and quantum computing creates new privacy and security problems. This study examines the critical need to prevent potential security concerns from quantum computing in IoT applications. We investigate the incorporation of quantum computing approaches within IoT security frameworks, with a focus on developing effective security mechanisms. Our research, which uses quantum algorithms and cryptographic protocols, provides a unique solution to protecting sensitive information and assuring the integrity of IoT systems. We rigorously analyze critical quantum computing security properties, building a hierarchical framework for systematic examination. We offer concrete solutions flexible to diverse as well as ambiguous opinions through using a unified computational model with analytical hierarchy process (AHP) multi-criteria decision-making (MCDM) as the technique for ordering preferences by similarity to ideal solutions (TOPSIS) in a fuzzy environment. This study adds practical benefit by supporting practitioners in recognizing, choosing, and prioritizing essential security factors from the standpoint of quantum computing. Our approach is a critical step towards improving quantumlevel security in IoT systems, strengthening their resilience against future threats, and preserving the IoT ecosystem’s long-term prosperity.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Blockchain Technology Applications and Security · IoT and Edge/Fog Computing · Cryptography and Data Security

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

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