An Architecture for Automated Verification of Academic Testimonials in E-Learning
Kh. Amirul Islam1, Akash Nag2, Sunil Karforma3, Sripati Mukhopadhyay4
1Kh. Amirul Islam, Research Scholar, Dept. of Computer Science, The University of Burdwan, India.
2Akash Nag*, Lecturer, Dept. of Computer Science, M.U.C. Women’s College, Burdwan, India.
3Sunil Karforma, Professor & Head, Dept. of Computer Science, The University of Burdwan, India.
4Sripati Mukhopadhyay, Prof., Dept. of Comp. Sc. & Engg., Academy of Technology, West Bengal, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 2377-2383 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7139118419/2019©BEIESP | DOI: 10.35940/ijrte.D7139.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Universities offering e-learning courses often provide their students with a hard copy of the marksheet. When that same student wants to apply for a job through the online application portal of a company, he/she must scan the marksheet and upload the scanned copy. This is a nuisance because there can be many such marksheets and not everyone has access to a scanner at home. The candidate is also required to provide the name of the University which issued the degree as well as the marks obtained, because these information cannot be extracted from the scanned marksheet image using OCR with 100% success rate due to many factors including: varying marksheet formats, presence of background watermarks, differing fonts, loss in quality during scanning, etc. The company must now manually verify each such application by matching the entered marks against the marks printed in the marksheet, which is a tedious process. In this paper, we propose an alternative approach where the data printed on the marksheet is also embedded in a digital copy of the marksheet. This digital copy, in the form of an image, can then be downloaded by the students from the University portal thereby eliminating the need for scanning. Furthermore, when this image is uploaded, the company, i.e. job provider, can easily verify the information by invoking a standard API exposed by the University (or some nodal agency), which will then extract the embedded information. This eliminates the need for any manual verification and the entire process is automated, simple, fast and hassle-free. Security features are also inherent in our approach thereby reducing any chances of fraud.
Keywords: Steganography, E-Learning, LSB Steganography, API.
Scope of the Article: E-Governance, E-Commerce, E-Business, E-Learning.