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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65062
Volume:
10 |
6 |
Jun 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Engineering
Sardar Patel Institute of Technology
Department of Computer Engineering
Sardar Patel Institute of Technology
Department of Computer Engineering
Sardar Patel Institute of Technology
Department of Computer Engineering
Sardar Patel Institute of Technology
Department of Computer Engineering
Sardar Patel Institute of Technology
With the rise of digital documents and online file-sharing platforms, keeping uploaded files secure and private has become a major challenge. Traditional file-sharing systems often offer limited control over how documents are accessed, viewed, or shared after distribution. This can lead to risks, including unauthorized access and the misuse of confidential information. This paper proposes a SecureVault, an intelligent file-sharing and OCR system, to create a safe and smart platform for uploading, managing, and sharing PDF documents and image files. The system includes secure authentication, permission-based access control, and Optical Character Recognition (OCR) techniques for automatic text extraction from uploaded documents. It is built using React.js for the frontend, Node.js and Express.js for backend services, and MongoDB for database management. Tesseract.js and PDF-Parse libraries are incorporated for OCR and text extraction functions. JWT authentication and encrypted password storage enhance security and privacy protection. Ex-perimental results show that this system effectively blends secure file sharing with OCR-based document processing for modern digital document management.
KEYWORDS
The proposed SecureVault: Intelligent File Sharing and OCR System merges secure document management, OCR-enabled intelligent text extraction, and access-controlled shar-ing of image and PDF documents. The system utilizes Tesser-act.js for OCR text extraction and employs JWT for secure authentication, combined with permission-based access control for secure document sharing. Results from tests indicated that the system can efficiently manage documents and offer secure and efficient text extraction and file sharing, and can be deployed in educational institutions, organizations, and healthcare and enterprise systems. In the future, additional features will be added, including, but not limited to, cloud storage integration, deployment via Docker, multilingual OCR features, AI-based document classification, advanced encryp-tion, and mobile application support. This system will also include scalable digital document management features.
[1] Smith, R.. (2007). An Overview of the Tesseract OCR Engine. Ninth In-ternational Conference on Document Analysis and Recognition (ICDAR 2007). 2. 629 - 633. 10.1109/ICDAR.2007.4376991. [2] Redmon, Joseph and Ali Farhadi. “YOLOv3: An Incremental Improve-ment.” ArXiv abs/1804.02767 (2018): n. pag. [3] Provos, Niels. (1999). A Future-Adaptable Password Scheme. [4] Gonzalez, R.C. and Woods, R.E. (2018) Digital Image Processing. 4th Edition, Pearson Education, New York, 1022 p. [5] Ravi S. Sandhu, Edward J. Coyne, Hal L. Feinstein, and Charles E. Youman. 1996. Role-Based Access Control Models. Computer 29, 2 (February 1996), 38–47. [1] He, K., Zhang, X., Ren, S. and Sun, J. (2016) Deep Residual Learn-ing for Image Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, 27-30 June 2016, 770-778. [2] Mihir P, Ritik D, Vivek V, Shrinit P, and Chandrayani Rokade, “Smart Document Management System using OCR”, IJPRSE, vol. 3, no. 05, pp. 32–35, May 2022. [3] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. 2017. Ima-geNet classification with deep convolutional neural networks. Commu-nications of the ACM 60: 84–90. [4] Peterson, John Mitchell, Brian Robinson, Kevin Clark, Steven Lewis, Thomas William, Bruce. (2023). Deep Learning-Based OCR for Automatic Extraction and Classification of Text from Retail Bill Receipts. [5] Varsha Jawale, Vedashri Jundre , Reshma Bathe, 2013, Secure Cloud Based Document Management System, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH TECHNOLOGY (IJERT) Volume 02, Issue 03 (March 2013),
Publication Date
6/16/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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