Development of a Blockchain-Based E-Commerce Platform Using Next.Js and Solana Blockchain Network (Published)
E-commerce has transformed global trade by increasing accessibility and convenience, but challenges such as fraud, data breaches, and high intermediary costs still affect trust and efficiency. In Nigeria, these issues are intensified by logistical barriers and low consumer confidence. This study developed a blockchain-based e-commerce platform using the Solana blockchain to enhance transparency, security, and cost efficiency. The system was built with Next.js and integrated with Solana for transaction execution, guided by a prototyping SDLC model. Core features included user authentication, product listings, secure payments, and merchant dashboards. Performance testing on Solana Playground showed an average throughput of 3.2 TPS and transaction confirmation times under one second, with costs below 0.015 SOL per transaction. The results demonstrate Solana’s capability for scalable, low-latency digital commerce, providing empirical evidence of blockchain’s potential for secure, real-time e-commerce operations in emerging markets like Nigeria.
Keywords: Blockchain, E-Commerce, scalability, solana, transparency
Leveraging User Behavior Analytics for Advanced E-Commerce Fraud Detection (Published)
E-commerce platforms face the critical challenge of balancing seamless customer experiences with robust security measures to prevent fraud. Traditional rule-based detection systems have proven increasingly inadequate against sophisticated threats, generating excessive false positives while missing complex fraud attempts. This article explores how behavioral analytics transforms fraud prevention by analyzing digital footprints customers leave while navigating online stores. By leveraging machine learning algorithms to establish behavioral baselines and detect anomalies, merchants can identify fraudulent activity with unprecedented accuracy while reducing false positives. The integration of behavioral indicators—including navigation patterns, transaction timing, historical consistency, and multi-factor behavioral authentication—enables dynamic risk profiling that distinguishes legitimate users from impostors even when credentials are compromised. The implementation architecture, business impacts, privacy considerations, and emerging technologies in behavioral fraud detection are explored, demonstrating how the intricacies of human behavior serve as reliable indicators of authentic user identity in the digital landscape.
Keywords: Authentication, Cybersecurity, E-Commerce, Fraud Prevention, behavioral biometrics