Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks

This paper studies the vulnerability of large-scale power systems to false data injection (FDI) attacks through their physical consequences. Prior work has shown that an attacker-defender bi-level linear program (ADBLP) can be used to determine the worst-case consequences of FDI attacks aiming to maximize the physical power flow on a target line. This ADBLP can be transformed into a single-level mixed-integer linear program, but it is hard to solve on large power systems due to numerical difficulties. In this paper, four computationally efficient algorithms are presented to solve the attack optimization problem on large power systems. These algorithms are applied on the IEEE 118-bus system and the Polish system with 2383 buses to conduct vulnerability assessments, and they provide feasible attacks that cause line overflows, as well as upper bounds on the maximal power flow resulting from any attack.Comment: 6 pages, 5 figure

False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition

This paper studies the vulnerability of phasor measurement units (PMUs) to false data injection (FDI) attacks. Prior work demonstrated that unobservable FDI attacks that can bypass traditional bad data detectors based on measurement residuals can be identified by detector based on low-rank decomposition (LD). In this work, a class of more sophisticated FDI attacks that captures the temporal correlation of PMU data is introduced. Such attacks are designed with a convex optimization problem and can always bypass the LD detector. The vulnerability of this attack model is illustrated on both the IEEE 24-bus RTS and the IEEE 118-bus systems.Comment: 6 pages, 4 figures, submitted to 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm

Enzymatic preparation and facile purification of medium-chain, and medium- and long-chain fatty acid diacylglycerols

High purity diacylglycerols (DAG) rich in medium-chain fatty acid diacylglycerols (MCD) and medium- and long-chain fatty acid diacylglycerols (MLCD) were prepared via the enzymatic esterification of monoacylglycerols (MAG) with caprylic acid followed by molecular distillation (MD), solvent fraction and low-temperature centrifugation. The content of DAG in the crude product was 44.8 ± 0.1%, under the selected esterification conditions, which were MAGs/caprylic acid mole ratio of 1:3, reaction temperature of 65 °C, reaction time of 30 min and enzyme load of 5 wt%. Subsequently, the one-step MD and solvent fraction in methanol/ethanol increased the DAG content to 61.3 ± 0.8%. Eventually, the product containing 86.6 ± 0.6% of DAG with 39.3 ± 1.3% of MCD and 47.3 ± 0.6% of MLCD was obtained by the methanol crystallization at 0 °C with a water content of 9 wt% and a 1:3 ratio of glycerides/methanol (v/v) followed by the centrifugation separation at 0 °C.The financial support from the National Natural Science Foundationof China under grants 31671781, 31371785 and 31501443, theNational Key Research and Development Program of China under grant2017YFD0400200, the Department of Science and Technology ofGuangdong Province under grants 2017B090907018 and2014A010107014, and the Bureau of Science and Information ofQingyuan under grant 2016D008 are gratefully acknowledged

How Does Fundraiser-claimed Product Innovation Influence Crowdfunding Outcomes

The crowdfunding platforms have always been dedicated to supporting and inspiring innovative, and creative campaigns. However, limited research has been done to examine the fundraiser-claimed product innovation in campaign descriptions and its relation to fundraising performance. In this paper, we aim to tackle this important yet understudied problem. More specifically, we adopt a deep learning-based approach to extract sentences that contain innovation claims from project descriptions. We then conduct an empirical analysis to study the relation between fundraiser-claimed product innovation and crowdfunding performance by using a large sample consisting of 11,521 projects collected from Kickstarter across 4 project categories. Findings show a statistically significant association between fundraiser-claimed product innovation and crowdfunding performance. Additionally, the number of focal project innovation claims has a curvilinear relationship (inverted ‘U’ shape) with crowdfunding performance. Our study contributes to both product innovation detection and crowdfunding literature by demonstrating the association between product innovation presentation and crowdfunding performance