Design and Evaluation of a Forensic-Ready Framework for Smart Classrooms
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| Publicado en: | International Journal of Advanced Computer Science and Applications vol. 16, no. 5 (2025) |
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| Autor principal: | |
| Publicado: |
Science and Information (SAI) Organization Limited
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 022 | |a 2158-107X | ||
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| 024 | 7 | |a 10.14569/IJACSA.2025.0160532 |2 doi | |
| 035 | |a 3222641157 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a PDF | |
| 245 | 1 | |a Design and Evaluation of a Forensic-Ready Framework for Smart Classrooms | |
| 260 | |b Science and Information (SAI) Organization Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 610 | 4 | |a National Institute of Standards & Technology | |
| 653 | |a Learning | ||
| 653 | |a Classrooms | ||
| 653 | |a Education | ||
| 653 | |a Monte Carlo simulation | ||
| 653 | |a Cybersecurity | ||
| 653 | |a Forensic computing | ||
| 653 | |a Blockchain | ||
| 653 | |a Retrieval | ||
| 653 | |a Technological change | ||
| 653 | |a Threats | ||
| 653 | |a Computer science | ||
| 653 | |a Architecture | ||
| 653 | |a Educational technology | ||
| 653 | |a Learning management systems | ||
| 653 | |a Automation | ||
| 653 | |a Access control | ||
| 653 | |a Internet of Things | ||
| 653 | |a Innovations | ||
| 653 | |a Machine learning | ||
| 653 | |a Data integrity | ||
| 653 | |a Forensic sciences | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Edge computing | ||
| 653 | |a Computer engineering | ||
| 653 | |a Design | ||
| 653 | |a Computer forensics | ||
| 653 | |a Structured Query Language-SQL | ||
| 773 | 0 | |t International Journal of Advanced Computer Science and Applications |g vol. 16, no. 5 (2025) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3222641157/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3222641157/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |