Publication

Abstract : Detecting anomalies is crucial in various fields such as cybersecurity, fraud prevention and healthcare monitoring. This study addresses anomaly detection in location-based systems by integrating blockchain technology and machine learning models. These anomalies occur in different contexts, like geographical monitoring and activity tracking. They include unusual movements, activities at odd times and user’s presence in unexpected locations. Machine learning and autoencoder models, are trained on GPS (Global Positioning System) coordinates and activity data to detect deviations from normal behaviour. Blockchain technology offers a decentralized platform for storing and managing user identities. Ganache is used for local blockchain implementation and deployment of smart contracts. Integrating blockchain for this use case ensures integrity, privacy and secure identity verification. Upon detecting an anomaly, an alert is sent to the concerned party only after their identity verification via blockchain, enhancing the reliability of anomaly detection systems, especially in scenarios where sensitive location data is involved.