Academic Document Authentication using Elliptic Curve Digital Signature Algorithm and QR Code

Wellem, Theophilus; Nataliani, Yessica; Iriani, Ade

doi:10.30630/joiv.6.2.872

Cited by 11 publications

(8 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the fundamentals above, several papers have implemented the digital signature method using various attributes. Wellem et al [25], utilized the standard elliptic curve digital signature algorithm (ECDSA). single signature method and QR code to address the vulnerability of paper-based academic documents by proposing a document authentication system.…”

Section: Comparison To Existing Methodsmentioning

confidence: 99%

“…For comparison, this study compared the proposed method with the methods proposed by Wellem et al [25], which uses the standard ECDSA single signature method, Bisheh-Niasar et al [26], with the EdDSA single signature method, and G. Shankar et al [14], with the EdDSA double signature method but using Aadhar numbers, fingerprints, and random numbers for the key generation process.…”

Section: Performance Assessmentmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Multi-signature and QR Code Integration for Document Authentication Using EdDSA-based Algorithm

2024

IJIES

View full text Add to dashboard Cite

The previous global pandemic has shifted many of these proposed needs to remote interactions, including document authentication. The solution for remote document authentication is the use of digital signatures. However, in reality, most implementations are inefficient and even weaken already secure methods. This study presents a novel efficient digital signature method based on a multi-signature method that incorporates the edwards-curve digital signature algorithm (EdDSA) algorithm, a quick-response (QR) code, and the cryptographically secure pseudorandom number generator (CSPRNG) for key generation. This study assessed the performance efficiency of this method by running it on a large number of executions in terms of generation, signature generation, and signature generation time for three signers and a verifier. The results show that this proposed method outperforms all the existing methods that this study compared across all parameters. In key generation performance assessments, this proposed method stands out by employing CSPRNG that already been proven for its efficiency and security for cryptographic use. The usage of the multi-signature method in the EdDSA algorithm has made this proposed method superior in signature generation and signature verification performance assessment. On paper, EdDSA is the latest algorithm that has surpassed its predecessors regarding security and efficiency. By using the multi-signature method, this study further improves the signature generation and signature verification efficiency as signatures only need to be generated and verified once to represent all signers. With the performance assessment done on this proposed device, this proposed method has an average improvement of 76.27% across all parameters against the existing method. Additionally, using QR codes in the method facilitates real-life signature verification by simplifying the scanning process for verifiers. This work provides a secure and efficient solution to document file authentication.

show abstract

Section: Comparison To Existing Methodsmentioning

confidence: 99%

Section: Performance Assessmentmentioning

confidence: 99%

Efficient Multi-signature and QR Code Integration for Document Authentication Using EdDSA-based Algorithm

2024

IJIES

View full text Add to dashboard Cite

show abstract

“…Machine learning is a technique for classifying and predicting new data by applying models to learn patterns from previous data sets [13]. Machine learning is also deployed because it can process data more effectively and efficiently [14].…”

Section: A Machine Learningmentioning

confidence: 99%

Modeling and Application of Credit Scoring Based on A Multi-Objective Approach to Debtor Data in PT. Bank Riau Kepri

Sugianto,

Widyasari,

Wardhani

2024

JOIV : Int. J. Inform. Visualization

View full text Add to dashboard Cite

The development of information technology in Indonesia, marked by the start of Industry 4.0, is very rapid. With the development of technology, many companies use technology to develop their business, one of which is banking, which analyses the process of prospective customers. New employees find it challenging to interpret and tend to agree more easily with prospective customers because they only see the fulfillment of general requirements. This research aims to find an overview of the primary and additional factors to analyze prospective credit customers using The Cross-Industry Standard Process for Data Mining (CRISP-DM). Develop a model in this study using data variables of prospective customers in health insurance as a moderating variable. This model tested the Decision Tree algorithm with an accuracy value of 92.49%, the Random Forest with an accuracy value of 81.72%, the Support Vector Machine (SVM) with an accuracy value of 91.25%, and K-Nearest Neighbor (K-NN) with an accuracy value. 90.58%, Gradient Boosting with an accuracy value of 90.69%, and XGBoost with an accuracy value of 93.27%. The algorithm uses a cross-validation technique at the validation stage by changing the K value to 2, 4, 6, 8, and 10. The results show that the XGBoost Algorithm accuracy is 93.27% with a K value of 8. As the highest model accuracy, this model was implemented using the XGBoost Algorithm.

show abstract

“…In [39], the researchers proposed a certificate verification system that uses a combination of QR codes and watermarks. The system embeds a unique watermark into each certificate that can be used to verify its authenticity.…”

Section: Literature Reviewmentioning

confidence: 99%

A Privacy-Centered Protocol for Enhancing Security and Authentication of Academic Certificates

Saleh¹,

Ghazali²,

Idris³

2023

IJACSA

View full text Add to dashboard Cite

Academic certificate authentication is crucial in safeguarding the rights and opportunities of individuals who have earned academic credentials. This authentication helps prevent fraud and forgery, ensuring that only those who have genuinely earned certificates can use them for education and career opportunities. With the increased use of online education and digital credentials in the digital age, the importance of academic certificate authentication has significantly grown. However, traditional techniques for authentication, such as QR code, barcode, and watermarking, have limitations regarding security and privacy. Therefore, proposing a privacy-centred protocol to enhance the security and authentication of academic certificates is vital to improve the trust and credibility of digital academic certificates, ensuring that individuals' rights and opportunities are protected. In this context, we adopted the Challenge Handshake Authentication (CHA) protocol to propose the Certificate Verification Privacy Control Protocol (CVPC). We implemented it using Python and Flask with a Postgres database and an MVT structure for the application. The results of the implementation demonstrate that the proposed protocol effectively preserves privacy during the academic certificate issuance and verification process. Additionally, we developed a proof of concept to evaluate the proposed protocol, demonstrating its functionality and performance. The PoC provided insights into the strengths and weaknesses of the proposed protocol and highlighted its potential to prevent forgery and unauthorised access to academic certificates. Overall, the proposed protocol has the potential to significantly enhance the security and authenticity of academic certificates, improving the overall trust and credibility of the academic credentialing system.

show abstract

Academic Document Authentication using Elliptic Curve Digital Signature Algorithm and QR Code

Cited by 11 publications

References 12 publications

Efficient Multi-signature and QR Code Integration for Document Authentication Using EdDSA-based Algorithm

Efficient Multi-signature and QR Code Integration for Document Authentication Using EdDSA-based Algorithm

Modeling and Application of Credit Scoring Based on A Multi-Objective Approach to Debtor Data in PT. Bank Riau Kepri

A Privacy-Centered Protocol for Enhancing Security and Authentication of Academic Certificates

Contact Info

Product

Resources

About