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

Guardado en:
Publicado en:International Journal of Advanced Computer Science and Applications vol. 16, no. 5 (2025)
Autor principal: PDF
Publicado:
Science and Information (SAI) Organization Limited
Materias:
National Institute of Standards & Technology
Learning
Classrooms
Education
Monte Carlo simulation
Cybersecurity
Forensic computing
Blockchain
Retrieval
Technological change
Threats
Computer science
Architecture
Educational technology
Learning management systems
Automation
Access control
Internet of Things
Innovations
Machine learning
Data integrity
Forensic sciences
Artificial intelligence
Edge computing
Computer engineering
Design
Computer forensics
Structured Query Language-SQL
Acceso en línea:Citation/Abstract
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Resumen: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.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2025.0160532
Fuente:Advanced Technologies & Aerospace Database