A Cloud-Native Full-Stack Java Framework for Secure and Transparent Online College Election Management on AWS

Abstract: The digitization of democratic processes within higher education institutions demands robust, scalable, and tamper-resistant platforms. Conventional paper-based and legacy digital election systems in academic environments are susceptible to vote manipulation, ballot stuffing, administrative overhead, and limited accessibility. This paper presents a cloud-native, full-stack election management framework designed specifically for college environments, deployed on Amazon Web Services (AWS) Elastic Beanstalk. The proposed system integrates a Spring Boot 3.x RESTful backend with a React-based single-page application (SPA) frontend, secured through JSON Web Token (JWT) stateless authentication, BCrypt-based password hashing (cost factor 12), and SHA-256 voter fingerprinting to enforce strict one-person-one-vote integrity. The relational data model, managed through Flyway versioned migrations on PostgreSQL 16, enforces vote immutability via database-level triggers, preventing any post-cast modification or deletion. Role-based access control (RBAC) segregates student voters from election officers, each operating within a strictly scoped permission boundary. The system supports complete election lifecycle management encompassing scheduling, active-period enforcement, result tallying, and controlled verdict publication. Experimental evaluation demonstrates sub-300 ms average API response times under concurrent load, zero duplicate-vote incidents across simulated test scenarios, and a fully automated CI/CD pipeline through AWS CodeBuild. The architecture is extensible to multi-institution environments and positions the framework as a replicable model for transparent, auditable academic e-governance.

Keywords: online voting system; cloud computing; AWS Elastic Beanstalk; JWT authentication; Spring Boot; role- based access control; SHA-256 fingerprinting; election management; academic e-governance; PostgreSQL