In order to solve the problem that traditional methods such as screening the electricity stealing suspect users rely on monthly power consumption change, abnormal line loss is of low efficiency and low accuracy rate; and the field investigation finds that act of electricity stealing is inefficient. This paper explores a new method in traditional anti-electricity stealing theory study and efficient anti-electricity stealing implementation using the massive data of current remote centralized meter reading, analyzes electricity stealing means and principles, draws a fishbone diagram of electricity stealing means, determines this paper’s research emphasis are under-voltage electricity stealing method and under-current electricity stealing method by statistical analysis of actual case. Electricity stealing decision algorithm is determined based on metering device wiring characteristics and voltage/current value law of high voltage power supply high voltage measurement users and high voltage power supply low voltage measurement users, outlier theory, an electricity stealing determining flowchart is drawn based on distance-based outlier detection method. Examples validate that the proposed algorithm and electricity stealing user selection process can fully identify electricity stealing users, providing a new idea to monitor staff for the accurate and timely anti-electricity stealing analysis with massive data of electricity information acquisition system.