Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …

Electricity theft has been a growing concern for the smart grid. It can be defined as follows:
illegal customers use energy from electric utilities without a contract or manipulate their …

Smart meters are key elements of a smart grid. These data from Smart Meters can help us
analyze energy consumption behaviour. The machine learning and deep learning …

Unlike the existing research that focuses on detecting electricity theft cyber-attacks in the
consumption domain, this paper investigates electricity thefts at the distributed generation …

In smart grids, homes are equipped with smart meters (SMs) to monitor electricity
consumption and report fine-grained readings to electric utility companies for billing and …

In advanced metering infrastructure (AMI), smart meters (SMs) are installed at the consumer
side to send fine-grained power consumption readings periodically to the system operator …

The smart grid advanced metering infrastructure (AMI) is vulnerable to electricity theft cyber-
attacks in which malicious smart meters report low readings to reduce the consumers' bills …

In the advanced metering infrastructure, smart meters are deployed at the consumers' side to
regularly transmit fine-grained electricity consumption readings to the system operator (SO) …

Data-driven electricity theft detectors rely on customers' reported energy consumption
readings to detect malicious behavior. One common implicit assumption in such detectors is …

In the smart grid, malicious customers may compromise their smart meters (SMs) to report
false readings to achieve financial gains illegally. This causes hefty financial losses to the …