Securing Smart Grid In-Network Aggregation through False Data Detection

Existing prevention-based secure in-network data aggregation schemes for the smart grids cannot e�ectively detect accidental errors and falsified data injected by malfunctioning or compromised meters. In this work, we develop a light-weight anomaly detector based on kernel density estimator to locat