Performance Analysis of Thf: a Novel Lightweight Cryptography Hash Function
Year: 2025
Type: article
Abstract: Cryptographic hash functions play a crucial role in contemporary information security systems, serving as foundational elements for ensuring data integrity and authentication in a wide array of applications. With the ever-growing demand for secure communication and robust data protection, there is a pressing need for hash functions that not only provide strong security guarantees but also operate efficiently in environments with limited computational and power resources. Existing cryptographic hash functions, such as SHA-2 and SHA-3, offer high security but often impose large computational overhead, making them unsuitable for resource-constrained environments. In addition, lightweight hash functions proposed in recent studies either compromise on security or fail to achieve optimal efficiency, leaving a gap in the development of balanced solutions. Recognizing this need, the authors previously introduced a novel lightweight cryptographic hash function, termed the Tiny Hash Function (THF), specifically designed to meet these constraints. This research article delves into an extensive performance analysis of THF, examining its efficiency, security, and suitability for use in resource-constrained settings. The study systematically evaluates THF in comparison to existing lightweight and standard hash functions, addressing critical aspects such as energy consumption, computational complexity, and resistance to cryptographic attacks. The analysis aims to validate THF's effectiveness in providing the desired security properties while maintaining minimal resource consumption, thereby making it an attractive choice for applications such as Internet of Things (IoT) devices, mobile platforms, and other scenarios where traditional hash functions may be impractical. By bridging the gap between security and efficiency, this study contributes to the advancement of cryptographic primitives tailored for modern lightweight computing environments.
Author: Journal of Theoretical and Applied Information Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7083582052
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