## 1 Introduction
As a result, a decentralized architecture is essential to provide ledger integrity, transparency, fully automated and online process mechanisms, communication node connectivity (P2P), and a completely traceable and secure infrastructure. However, the involvement of root stakeholders in the process of certificate issuance and accreditation includes (i) the Federal Education Ministry (FEM), (ii) the HED, (iii) registered universities, (iv) the accreditation department, and (v) candidates. Candidate credential verification and a quick accreditation process are two examples of how blockchain distributed ledger technology can help with online learning, development, and management, including easy and secure verification [13]. The blockchain also allows for tamper-proof examination of registered accreditation versions of records. This process guarantees the privacy and protection of the recorded credentials of the marked certificate. Further, the system does not charge the extra cost of availability, security, and maintenance level of provenance pertinent to storing the accreditation details with addresses [14]. With the collaboration of machine learning, especially artificial neural networks with blockchain technology, the mechanism of credential classification and verification will be more robust. For example, hyperledger sawtooth has provided a modular enterprise infrastructure that acts on a consortium network architecture for intelligent public-private communication and connectivity [15]. Through the edge devices, the HED engineer handles a diverse range of accreditation scheduling, monitoring, and maintenance of delivery and preservation protocols and automates a configurable customized structure that enables optimization, versatility, and innovation as well [15]. For ledger protection, SHA-256 hash-based encryption mechanisms support chaincodes that are designed and implemented using the distributed general-purpose language (Go/Java). A consortium network design includes the trustworthy execution of educational node transactions and a pluggable consensus protocol with efficient pre-defined fault tolerance. However, the main concern of this paper is to address the limitations and issues of accreditation credential evaluation and verification using blockchain-machine learning collaborative technology. This paper proposes a novel collaborative model of machine learning and blockchain hyperledger sawtooth-enabled secure accreditation analysis procedure for investigating if a certificate credential is tamper-proof and verifying process credibility for the Higher Education Department. In this process, a ministry of education is responsible for managing the process of higher education accreditation for efficient certificate credentials verification and issuing by affiliated HED-recognized universities. The proposed modular solution used hyperledger sawtooth (a consortium structure) to design and deploy a hybrid hyperledger network, which is based on public (for candidate application scenario) and private (to maintain ledger privacy between stakeholders) networks. Several participating members are analyzed and registered to the consortium network, to achieve integrity, confidentiality, privacy, secrecy, and provenance. Moreover, this solution also covers the ledger protection scenario, such as hash-encrypted (SHA-256) based distributed ledger storage in the immutable preservation (IPFS) performed on the network in a chronological form. The main contribution of the paper is as follows:  
* In this paper, a secure process of accreditation/credential verification and investigation of the certificate credibility is presented. An analysis of the forge proof and tampering aspects of the issuance certificate is presented. * A secure analytical model is proposed for accreditation credential analysis, such as matching the content of the original issuance certificate with the verifiable one by using machine learning techniques, especially artificial neural networks (ANNs).