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arXiv · 2504.04063

Analysis of Light-Weight Cryptography Algorithms for UAV-Networks

Abstract

Unmanned Aerial Vehicles are increasingly utilized across various domains, necessitating robust security measures for their communication networks. The ASCON family, a NIST finalist in lightweight cryptography standards, is known for its simplistic yet resilient design, making it well-suited for resource-constrained environments characterized by limited processing capabilities and energy reservoirs. This study focuses on understanding the integration and assessment of the ASCON encryption algorithm in UAV networks, emphasizing its potential as a lightweight and efficient cryptographic solution. The research objectives aim to evaluate ASCON variants' effectiveness in providing security comparable to AES-128 while exhibiting lower computational cost and energy consumption within simulated UAV network environments. Comparative analysis assesses performance metrics such as encryption and decryption speeds, resource utilization, and resistance to cryptographic vulnerabilities against established algorithms like AES. Performance metrics, including peak and average execution times, overall throughput, and security properties against various cryptographic attacks, are measured and analysed to determine the most suitable cryptographic algorithm for UAV communication systems. Performance results indicate that ASCON-128a as the optimal choice for UAV communication systems requiring a balance between efficiency and security. Its superior performance metrics, robust security properties, and suitability for resource-constrained environments position it as the preferred solution for securing UAV communication networks. By leveraging the strengths of ASCON-128a, UAV communication systems can achieve optimal performance and security, ensuring reliable and secure communication in challenging operational environments.

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BibTeXRIS

Aanchal Patel, Aswani Kumar Cherukuri. 2025-04-05. Analysis of Light-Weight Cryptography Algorithms for UAV-Networks. https://arxiv.org/abs/2504.04063

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