000			01418nam a2200169 a 4500
005			20260901030337.0
008			250101s2019 xx o 000 0 eng d
100	1		_aYachen Tang
245	1	0	_aInference of Tampered Smart Meters with Validations from Feeder-Level Power Injections
264		1	_barXiv _c2019
336			_atext
338			_aonline resource
520			_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
506	0		_aOpen access — freely available to read.
856	4	0	_uhttps://arxiv.org/pdf/1904.13208v1 _yRead the full paper (PDF)
942			_cERES
999			_c655 _d655