Abstract
In with the proliferation of smart grid research, the Advanced Metering Infrastructure (AMI) has turn into the initial ever-present and permanent platform for performing computational operations. On the other hand, due to the restricted uniqueness of AMI, such as difficult network structure, data with privacy sensitivity and smart meter with resource constrained mechanism it is an particularly challenging issue for the AMI security. Power theft is one of the most significant concerns connected to the implementation strategy of smart grid. The utility companies lose more than $15 billion every year due to power theft around the world based on the estimation data gathered. To address this challenge, in this paper, we talk about the background of AMI and identify major security requirements that AMI should meet. Specifically, an attack tree based threat model is first offered to demonstrate the power-theft behaviors in AMI. Then, we summarize the current AMI power-theft detection schemes into three categories, i.e., classification-based, state estimation-based and game theory-based ones, and make wide-ranging comparisons and discussions on them. In order to provide a deep understanding of security vulnerabilities and solutions in AMI and shed light on future research directions. The Household data automatically reading is important in the process of power system information. It is also an urgent problem that power industries want to solve because the exactness and real time of meter data copy have an effect on the power system information level, management decisions, and economic benefits. Recently there have been numerous reports concerning the automatic energy meter reading.
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