01573nam a2200181 a 450000500170000000800400001710000160005724500910007326400160016433600090018033800200018952009050020950600460111485600660116094200090122699900130123595201430124820260901030337.0250101s2019    xx     o     000 0 eng d1 aYachen Tang10aInference of Tampered Smart Meters with Validations from Feeder-Level Power Injections 1barXivc2019  atext  aonline resource  aTampering of metering infrastructure of an electrical distribution system can significantly cause customers' billing discrepancy. The large-scale deployment of smart meters may potentially be tampered by malware by propagating their agents to other IP-based meters. Such a possibility is to pivot through the physical perimeters of a smart meter. While this framework may help utilities to accurately energy consumption information on the regular basis, it is challenging to identify malicious meters when there is a large number of users that are exploited to vulnerability and kWh information being altered. This paper presents a reconfiguration switching scheme based on graph theory incorporating the concept of distributed generators to accelerate the anomaly localization process within an electrical distribution network. First, a data form transformation from a visualized grid topology to a 0 aOpen access — freely available to read.40uhttps://arxiv.org/pdf/1904.13208v1yRead the full paper (PDF)  cERES  c655d655  001040738CYBaMAINbMAINcSCICOMPd2026-09-01l0pYGE000916r2026-09-01 03:03:37uhttps://arxiv.org/pdf/1904.13208v1w2026-09-01yPAPER