SmartGate: A Prototype of AI–Blockchain-Enabled Academic Certificate Management System

Technological innovations have exposed vulnerabilities in traditional certificate verification systems. Conventional methods of verification cannot handle complex, evolving fraud systems and are susceptible to manipulation and human error. They can verify the authenticity of validly signed certificates but fail to detect behavioral fraud throughout the certificate lifecycle. This paper presents SmartGate—a secure framework that combines AI and blockchain to detect behavioral fraud and protect the integrity of academic certificates. The framework uses AI and feature engineering to capture user behavioral patterns indicative of fraud. The proposed SmartGate is designed to screen a certificate’s behavioral context before allowing it to be stored on the blockchain. University student records data were used to evaluate the proposed SmartGate. Specifically, the normal academic records and certificate workflow are real, while the suspicious cases were synthetically generated via controlled fraud scenarios. A machine learning algorithm is used to model the relationship between user behavior and the legitimacy of certificates. The framework introduces an SHAP explainable AI approach to interpret the outcomes for transparency and trust. To provide a secure, tamper-proof system, blockchain is deployed to anchor the approved certificates. A prototype of the proposed SmartGate has been developed. As a proof-of-concept implementation, the XGBoost model was used to validate the certificate-screening stage of the proposed SmartGate system. Also, a local Ethereum environment was used to implement the blockchain anchoring stage. Experimental results demonstrate the technical feasibility of the proposed SmartGate framework, including its ability to provide feature-level model explainability, within a controlled environment.