EduCrypt : a secure file data sharing platform using hybrid encryption for cloud-based e-learning

Arniaty, Andi and Safitri, Riri and Murbawisesa, Lambda Sangkala (2026) EduCrypt : a secure file data sharing platform using hybrid encryption for cloud-based e-learning. Jurnal Al-Azhar Indonesia Seri Sains dan Teknologi, 11 (1). pp. 1-16. ISSN 2355-8059

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Official URL: https://jurnal.uai.ac.id/index.php/SST/article/vie...

Abstract

The rise of cloud-based learning environments has transformed education but has also exposed vulnerabilities in data security. Learning Management Systems (LMSs) often handle sensitive academic data without adequate protection, leaving it vulnerable to unauthorized access and data breaches. This study introduces EduCrypt, a secure file-sharing platform that uses hybrid encryption, combining AES for fast data encryption and RSA for secure key exchange. In this research, a Hybrid Waterfall–Iterative method was used as the overarching research methodology to guide requirements analysis, architectural design, system implementation, and evaluation. EduCrypt integrates seamlessly with Moodle LMS via token-and credential-based authentication. Its architecture includes asynchronous RabbitMQ workers for efficient synchronization and a user-friendly web interface for secure file operations. Benchmark tests demonstrate stable encryption and decryption times under 300 ms for files up to 30 MB, showcasing bothscalability and efficiency. Security evaluations confirm that EduCrypt effectively mitigates brute-force attacks, SQL injection, and man-in-the-middle attacks. This research resulted in a validated enhancement in file security practices for LMS through the implementation of a hybrid cryptographic model. Furthermore, the outcome includes a fully functional EduCrypt prototype integrated with Moodle, along with performance and security evaluation results.

Item Type: Article
Uncontrolled Keywords: Data Security, Hybrid encryption, File sharing, E-learning, Cloud computing.
Subjects: 000 Computer science, information & general works > 000 Computer Science, Information, General Works
000 Computer science, information & general works > 000 Computer Science, Information, General Works > 005 Computer Programming, Programs, Data
Divisions: Universitas Al-Azhar Indonesia (UAI) > Fakultas Sains dan Teknologi (FST)
Depositing User: Mia Asmiati
Date Deposited: 06 Nov 2026 04:15
Last Modified: 06 Nov 2026 04:15
URI: http://eprints.uai.ac.id/id/eprint/2655

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