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Advancing IoT Security: Cryptographic Enhancements and Open Challenges

Year: 2025

Type: article

Abstract: The tremendous increase of data produced by Internet of Things (IoT) networks emphasizes how important to have robust security mechanisms in place to guarantee authenticity, integrity, and confidentiality. Due to inherent limitations of IoT devices, like limited memory, computing power, and energy consumption, they are particularly vulnerable to security threats and attacks. This paper comprehensively surveys possible cryptographic solutions to enhance IoT cybersecurity, discusses cryptographic algorithm classification, implementation problems, and performance parameters in the IoT ecosystem. This study explores common cryptographic optimization techniques using meta-heuristic algorithms (MHA), machine learning (ML), and blockchain (BC). A taxonomy of emerging technology solutions was demonstrated based on IoT security issues. Additionally, the paper explores cryptographic improvement challenges in the IoT environment with possible solutions.

Source: ZANCO Journal of Pure and Applied Sciences

DOI: 10.21271/zjpas.37.5.7

Authors: Jawaher Abdulwahab Fadhil, Marwan Aziz Mohammed

Institutions: Duhok Polytechnic University, Akre University for Applied Sciences, Knowledge University, Salahaddin University-Erbil

Language: English

Topic: Cryptographic Implementations and Security

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4415749049

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