A Hybrid Framework for Phishing Email Detection and Secure Communication Using AI and Blockchain

Abstract

One of the most prevalent and harmful forms of cybercrime remains phishing, which is often based on email as its primary avenue of attack. Traditional detection methods apply both rule-based filtering as well as machine learning classifiers, though they often come with large false-positive rates and no defense against message authenticity. To enhance the communication trust and detection accuracy, this paper proposes a hybrid framework integrating blockchain technology with artificial intelligence (AI). The AI module utilizes machine learning models trained with a labeled dataset of phishing, spam, and legitimate emails. The high performance of classification is evidenced by the experimental results, where up to 98.4% accuracy is achieved in binary classification and 97% accuracy for multiclass detection. A Solidity-based smart contract deployed on an Ethereum testnet irrevocably keeps hashed records of authenticated emails to ensure integrity and non-repudiation. This hybrid approach compares favorably with AI-only approaches in that it reduces false positives by as much as 35% and has traceability and tamper-resistant logging that blockchain-only approaches do not have. The results show that the integration of blockchain technology and artificial intelligence (AI) is a feasible method of secure and trustworthy email communication by balancing detection efficiency and protection of privacy.