Design and Evaluation of a Forensic-Ready Framework for Smart Classrooms

Abstract

The rise of cyber threats in educational environments underscores the need for forensic-ready systems tailored to digital learning platforms like smart classrooms. This study proposes a proactive forensic-ready framework that integrates threat estimation, risk profiling, data identification, and collection management into a continuous readiness cycle. Blockchain technology ensures log immutability, while LMS APIs enable systematic evidence capture with minimal disruption to learning processes. Monte Carlo Simulation validates the framework’s performance across key metrics. Results show a log capture success rate of 77.27%, with high accuracy for structured attacks such as SQL Injection. The system maintains operational efficiency, adding only 15% average CPU overhead. Forensic logs are securely stored in JSON format on a blockchain ledger, ensuring both integrity and accessibility. However, reduced effectiveness for complex attacks like Remote Code Execution and occasional retrieval delays under heavy loads highlight areas for improvement. Future enhancements will focus on expanding threat coverage and optimizing log retrieval. By addressing vulnerabilities unique to smart classrooms, such as unauthorized access and data manipulation, this study introduces a scalable, domain-specific solution for enhancing forensic readiness and cybersecurity in educational ecosystems.