With the proliferation of smart grid research, the Advanced Metering Infrastructure (AMI) has become the first ubiquitous and fixed computing platform. However, due to the unique characteristics of AMI, such as complex network structure, resource-constrained smart meter, and privacy-sensitive data, it is an especially challenging issue to make AMI secure. Energy theft is one of the most important concerns related to the smart grid implementation. It is estimated that utility companies lose more than $25 billion every year due to energy theft around the world. To address this challenge, in this paper, we discuss the background of AMI and identify major security requirements that AMI should meet. Specifically, an attack tree based threat model is first presented to illustrate the energy-theft behaviors in AMI. Then, we summarize the current AMI energy-theft detection schemes into three categories, i.e., classification-based, state estimation-based, and game theory-based ones, and make extensive 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, we also explore some open challenges and potential solutions for energy-theft detection.

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Fully sequential ranking-and-selection (R&S) procedures to find the best from a finite set of simulated alternatives are often designed to be implemented on a single processor. However, parallel computing environments, such as multi-core personal computers and many-core servers, are becoming ubiquitous and easily accessible for ordinary users. In this paper, we propose two types of fully sequential procedures that can be used in parallel computing environments. We call them vector-filling procedures and asymptotic parallel selection procedures, respectively. Extensive numerical experiments show that the proposed procedures can take advantage of multiple parallel processors and solve large-scale R&S problems.

We consider optimal capital allocation and managerial compensation mechanisms for decentralized¯rms when division managers have an incentive to misrepresent project quality and to minimize privately costly but value-enhancing e®ort. We show that in the optimal mechanism¯rms always underinvest in capital relative to a naive application of the net present value (NPV) rule. We make a number of novel cross-sectional predictions about the severity of the underinvestment problem and the composition of managerial compensation contracts. We also¯nd that¯rms will optimally give greater performance-based pay (at the expense of¯xed wages) to managers of higher quality projects to mitigate the incentive for managers to overstate project quality. Thus, managers may receive greater performancebased pay because they manage higher-quality projects, not that greater performance-based pay causes¯rm value to increase. ¤ We thank an anonymous referee,