Academic Document Authentication using Elliptic Curve Digital Signature Algorithm and QR Code - Wellem, Theophilus; Nataliani, Yessica; Iriani, Ade (JOIV : International Journal on Informatics Visualization, 2022)
Paper-based documents or printed documents such as recommendation letters, academic transcripts, and diplomas are prone to forgery. Several methods have been used to protect them, such as watermarking, security holograms, or using paper with specific security features. This paper presents a document authentication system that utilizes QR code and ECDSA as the digital signature algorithm to protect this kind of document from counterfeiting. A digital signature is a well-known technique in modern cryptography used for providing data integrity and authentication. The idea proposed herein is to put a QR code in the printed documents where the QR code includes a digital signature. The signature can later be authenticated using the proposed system by uploading the document for authentication or scanning the document's QR code. The proposed system is particularly developed for digital signature generation and verification of students' final project approval documents as the case study. In traditional settings, the approval form is typically signed directly by the student's advisor dan co-advisor using handwritten signatures. However, using the conventional handwritten signature, the signature on the approval form can be falsified. Therefore, a digital signature generation and verification system is implemented herein to avoid handwritten signature falsification. The advisors can use this system to sign the approval form using a digital signature instead of a handwritten one. The signature is stored in a QR code and is generated using ECDSA with SHA-256 as the hash function. The proposed system is evaluated using documents (i.e., approval forms) with genuine and forged QR codes.Â  The evaluation results showed that the system could verify the authenticity of the approval forms, which contain genuine QR codes. The approval forms that contained forged QR codes were correctly identified.