Secure degree attestation and traceability verification based on zero trust using QP-DSA and RD-ECC
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.spl-2.30Keywords:
Degree attestation, Blockchain, Data encryption, Smart contract, Hash-based message authentication code, Elliptic curve cryptography, Higher education credentials.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The process of rendering authenticity to the Degree Certificate (DC) is known as Degree Attestation (DA). None of the prevailing works have focused on zero trust-based DA, verification, and traceability for secured DA. So, zero trust-based secured DA, verification, and traceability of degree credentials are presented in the paper. Primarily, to upload the DC of the student, the university registers and logs in to the Blockchain (BC). Subsequently, by utilizing radioactive decay-based elliptic curve cryptography (RD-ECC), the DC is secured. Next, by utilizing Glorot initialization-based Proof-of-Stake (GPoS), the data is stored in the BC. Further, to verify the traceability of the data, a Smart Contract (SC) is created. In the meantime, the student registers and logs in to the BC and gives attestation requests to the university. By utilizing rail fence cipher (RFC) RD-ECC hash-based message authentication code (RFCR-HMAC), the university authenticates the request. By utilizing a quadratic probing-based digital signature algorithm (QP-DSA), the university attests the DC after authentication. Lastly, by utilizing RD-ECC, the attested certificate is encrypted and sent to the student. Hence, the certificate is secured with an encryption time (ET) of 5971ms and DA is performed with a Signature Generation Time (SGT) of 6637ms.Abstract
How to Cite
Downloads
Similar Articles
- P Janavarthini, I Antonitte Vinoline, Sustainable fuzzy inventory for concurrent fabrication and material depletion modeling with random substandard items , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, A resilient supply chain model integrating demand variability and carbon emissions in imperfect production systems , The Scientific Temper: Vol. 16 No. 08 (2025): The Scientific Temper
- Rajesh Rayal, H.K. Joshi, Deeksha Kapruwan, Neelam Shah, Shraddha Bharti, Sakshi Saxena, Reproductive Capacity of Noemacheilus rupicola and Sex Ratio from River Yamuna, Uttarakhand, India , The Scientific Temper: Vol. 13 No. 01 (2022): The Scientific Temper
- Seema Rani Sarraf, S.N. Dubey, STRESS AND ACADEMIC ACHIEVEMENT IN RELATION TO DURATION OF SLEEP AND COURSE , The Scientific Temper: Vol. 8 No. 1&2 (2017): The Scientific Temper
- Deepa ., Anju Panwar, Anju Panwar, Yougesh Kumar, Morphological Redescription of the Spinitectus notopteri Karve and Naik, 1951 from the Bronze Featherback Notopterus notopterus (Pallas, 1769) from Muzaffarnagar (U.P.), India , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
- Leyla A.A Abu-Hussein, The role of food program to overcome obesity, overweight, and underweight among autistic children , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
You may also start an advanced similarity search for this article.

