AI-Driven Cybersecurity and Functional Framework for Remote Laboratories: A Software Engineering Perspective

Remote laboratories have reshaped the way engineering courses provide hands-on experimentation by enabling students to control physical lab equipment via online interfaces. nevertheless, their ease, However, these platforms face challenges such as security vulnerabilities, performance instability, and limited user support. This paper introduces a layered framework that integrates artificial intelligence (AI) into a secure, modular design. Using conventional software engineering techniques, our approach improves cybersecurity through intelligent threat detection, automated resource balancing, and context-aware user interaction. We provide a comprehensive explanation of the framework's architecture, which methodically addresses critical requirements. This includes a proactive cybersecurity apparatus that adapts to emergent threats, as well as real-time device control and data acquisition. Ultimately, this work aims to assist educators and institutions build or modernize remote lab environments that offer robust protection and seamless learning outcomes, even under rapidly shifting demands.