Paper Title
Smart Detection of False Energy Readings Using Cloud-Based Services

Abstract
There are new difficulties associated with the growing use of smart energy meters for real-time electricity monitoring, particularly about data security and integrity. False reading attacks that manipulate energy usage data are one of the major problems utility suppliers confront. Using Firebase as the primary data platform, this study presents a scalable and effective method for identifying erroneous readings in smart energy meters. The system gathers meter readings continually, saves them in the Firebase real-time database, and flags worrisome numbers using statistical and rule-based anomaly detection methods. The suggested methodology greatly shortens the response time to any threats by utilizing Firebase's cloud architecture to enable rapid data synchronization, remote monitoring, and warning creation. The approach's resilience and dependability are confirmed by the experimental validation, which makes it a useful addition to smart grid cybersecurity. Keywords - Smart Grid Security, False-Reading Attacks, Net-Metering System, IoT-Based Monitoring, Firebase Real-Time Database, Real-Time Monitoring, False Reading Detection, Real-Time Alerts