Smart grid is a cyber-physical system which integrates communication networks into traditional power grid. This integration, however, makes the power grid susceptible to cyber attacks. One of the most distinguished challenges in studying the aftermath of cyber attacks in smart grid lies in data-centric threats. Even though such attacks are critical to the information network, they will result in much more Domino-like impact than they behave in cyber world. This is because for an informationcentric network, distorted or delayed information undermines services and applications. But in power grid, these data-centric attacks may result in instable power systems, and further detrimental impact of power supplies. In this paper, we present Greenbench, a benchmark that is designed to evaluate real-time power grid dynamics in response to data-centric attacks. The simulation results provide several counter-intuitive suggestions to both smart grid security research and deployment.
Law enforcement agencies take extreme caution when it comes to the selection of the image acquisition devices for evidence photography. For example, there was a large gap between when the digital camera was invented and when it became popularly used, and when it was adopted by law enforcement agencies to capture images for the documentation of crime scenes and physical evidence. Similarly, although smartphones are commonly used for taking photos and are gradually replacing digital cameras to become the mostly used photography devices, using smartphones for evidence photography is still uncommon among law enforcement agencies. In this article, we discuss a particular use scenario of smartphone photography, that is, using a smartphone to capture images of latent fingerprints. To collect experimental data, images of fingerprints were taken by a standard digital SLR camera and a smartphone camera. The numerical values representing the fingerprint qualities of these two sets of images were then generated by a Biometric SDK software. From the comparison of the quantitative image quality results, we concluded that no statistically significant difference was found between the two image acquisition devices. Our experimental data shed light on the perspective of adopting smartphones as competent devices for the purpose of latent fingerprint photography at a crime scene.
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