  Citation: Shaikh, Z.A.; Khan, A.A.; Baitenova, L.; Zambinova, G.; Yegina, N.; Ivolgina, N.; Laghari, A.A.; Barykin, S.E. Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture. Appl. Sci. 2022, 12, 2534. https://doi.org/10.3390/ app12052534 Academic Editor: Pericle Perazzo Received: 28 January 2022 Accepted: 26 February 2022 Published: 28 February 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). applied sciences Article Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture Zaffar Ahmed Shaikh 1 , Abdullah Ayub Khan 1,2, * , Laura Baitenova 3 , Gulmira Zambinova 4 , Natalia Yegina 5 , Natalia Ivolgina 6 , Asif Ali Laghari 2, * and Sergey Evgenievich Barykin 7 1 Faculty of Computing Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi 75660, Sindh, Pakistan; zashaikh@bbsul.edu.pk 2 Department of Computer Science, Sindh Madressatul Islam University, Karachi 74000, Sindh, Pakistan 3 Almaty University of Power Engineering and Telecommunications (AUPET) Named after G.Daukeev, Almaty 050013, Kazakhstan; baitenova_laura@mail.ru 4 Kazakh University of Economics, Finance and International Trade, Nur-Sultan 010005, Kazakhstan; gulmira_6969@mail.ru 5 Department of Economics, Ogarev Mordovia State University, 430005 Saransk, Russia; avantacom@mail.ru 6 Plekhanov Russian University of Economics, 115903 Moscow, Russia; nataly55550@yandex.ru 7 Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia; sbe@list.ru * Correspondence: abdullah.ayub@bbsul.edu.pk (A.A.K.); asif.laghari@smiu.edu.pk (A.A.L.) Abstract: This paper proposes a novel and secure blockchain hyperledger sawtooth-enabled consor- tium analytical model for smart educational accreditation credential evaluation. Indeed, candidate academic credentials are generated, verified, and validated by the universities and transmitted to the Higher Education Department (HED). The objective is to enable the procedure of credential verification and analyze tamper-proof forged records before validation. For this reason, we designed and created an accreditation analytical model to investigate individual collected credentials from universities and examine candidates’ records of credibility using machine learning techniques and maintain all these aspects of analysis and addresses in the distributed storage with a secure hash- encryption (SHA-256) blockchain consortium network, which runs on a peer-to-peer (P2P) structure. In this proposed analytical model, we deployed a blockchain distributed mechanism to investigate the examiner and analyst processes of accreditation credential protection and storage criteria, which are referred to as chaincodes or smart contracts. These chaincodes automate the distributed credential schedule, generation, verification, validation, and monitoring of the overall model nodes’ transac- tions. The chaincodes include candidate registration with the associated university (candidateReg()), certificate-related accreditation credentials update (CIssuanceTrans()), and every node’s transactions preservation in the immutable storage (ULedgerAV()) for further investigations. This model simulates the educational benchmark dataset. The result shows the merit of our model. Through extensive sim- ulations, the blockchain-enabled analytical model provides robust performance in terms of credential management and accreditation credibility problems. Keywords: blockchain; hyperledger sawtooth; machine learning; artificial neural network; consor- tium network; certificate credentials accreditation 1. Introduction Certificate issuance and pre-verification by Higher Education Department (HED) recognized universities play a vital role in developing a platform and opportunities to pre-verify issued certificates through the e-portal mechanism. This scenario uplifts the educational turnaround, which directly impacts the economy and a skilled workforce with social mobility to promote and achieve the well-being of educationalists around the Appl. Sci. 2022, 12, 2534. https://doi.org/10.3390/app12052534 https://www.mdpi.com/journal/applsci