Abstract

With the quick integration of digital solutions in healthcare systems, the importance of cybersecurity has become a significant concern in safeguarding sensitive patient data against cyber threats. This paper presents a novel approach to enhance the security of healthcare systems through the integration of blockchain technology and AI-based anomaly detection, thereby reducing the risk of brute force attacks. The system utilizes the Ethereum blockchain, offering a decentralized and tamper-proof nature that is used as an authentication mechanism for both the patient and the doctor. A secure and friendly web interface is developed for registration and login purposes, which allows users to log in where data integrity is preserved via blockchain smart contracts. Additionally, doctors can upload medical data, like patient reports, to IPFS (via Pinata), ensuring decentralized and secure storage. To enhance security, we use supervised machine learning algorithms and apply random forest to detect brute force attacks on user accounts. Our AI model smartly separates lawful user access from unauthorized access by looking out for login patterns and suspicious activity. The system is evaluated using precision, recall, F1-score, and ROC-AUC metrics. The system’s accuracy is so precise that it accurately distinguishes between brute force attacks and legitimate logins. Our proposed solution provides a user-friendly interface, enables stakeholders to interact efficiently with their data, and protects their accounts from unauthorized access.