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<p>Augmented reality applications in edge computing environments require secure, real-time interaction between users and infrastructure. However, existing authentication protocols often suffer from significant drawbacks, including high computational overhead, increased latency, and susceptibility to security threats such as impersonation and replay attacks. These issues compromise system performance, user privacy, and seamless collaboration. To address these limitations, this research presents a novel anonymous authentication protocol for AR systems with edge computing, combining piecewise linear chaotic maps, physically unclonable functions, and a Hybrid Snooker Artificial Protozoan Optimization Algorithm (HSAPOA). It is the first to integrate chaos theory, hardware-level security, and bio-inspired optimization into a unified, lightweight framework, enhancing security and reducing computational overhead. Comprehensive performance evaluations confirm the protocol’s superiority over existing methods, achieving a communication cost of 200 bits, a communication overhead of 5500 bits, an execution time of 29.12&#xa0;ms, and a latency of 0.08&#xa0;s. Security analyses demonstrate resistance to common attacks such as replay, impersonation, and man-in-the-middle attacks. The proposed protocol offers a lightweight, scalable, and privacy-preserving authentication framework that significantly enhances secure user engagement in mobile AR environments supported by edge computing.</p>

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Hybrid snooker artificial protozoa optimization-based authentication protocol for secure edge augmented reality

  • 期刊论文

  • 发表日期：

    2026年2月25日

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  • Swapnil Saurav,
  • D. V. N. Siva Kumar,
  • K. S. Sudeep

摘要

Augmented reality applications in edge computing environments require secure, real-time interaction between users and infrastructure. However, existing authentication protocols often suffer from significant drawbacks, including high computational overhead, increased latency, and susceptibility to security threats such as impersonation and replay attacks. These issues compromise system performance, user privacy, and seamless collaboration. To address these limitations, this research presents a novel anonymous authentication protocol for AR systems with edge computing, combining piecewise linear chaotic maps, physically unclonable functions, and a Hybrid Snooker Artificial Protozoan Optimization Algorithm (HSAPOA). It is the first to integrate chaos theory, hardware-level security, and bio-inspired optimization into a unified, lightweight framework, enhancing security and reducing computational overhead. Comprehensive performance evaluations confirm the protocol’s superiority over existing methods, achieving a communication cost of 200 bits, a communication overhead of 5500 bits, an execution time of 29.12 ms, and a latency of 0.08 s. Security analyses demonstrate resistance to common attacks such as replay, impersonation, and man-in-the-middle attacks. The proposed protocol offers a lightweight, scalable, and privacy-preserving authentication framework that significantly enhances secure user engagement in mobile AR environments supported by edge computing.