A new system for identifying potential Internet threats has been developed by researchers at the University of Texas (UT) at Dallas. Designed to analyze behavioral data, the system monitors network traffic and provides an alert when it notices worrisome deviations in normal activity. “We proposed a novel platform that thoroughly analyzes network traffic behavior to identify potential Internet threats,” says UT Dallas professor Mehrdad Nourani. The technology uses two subsystems that work in parallel to reach a high speed and use memory efficiently, which allows for faster results and optimal use of resources. A bell-shaped curve of normal activity is built, and it can achieve nearly zero false positives and negatives when identifying abnormalities outside the curve. Nourani says the technology also could be used to analyze health data and detect abnormal health issues such as heart arrhythmia, sleep apnea, or epileptic seizure.
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Kavli Institute of Nanoscience researchers have developed a way to use water to quickly transfer layers from one surface to another by exploiting the fact that different materials have different hydrophilicity, a discovery that could lead to lower manufacturing costs for nanoelectronics. The researchers, led by Kavli’s Gregory Schneider and Cees Dekker, developed a solid hydrophobic layer on top of a silicon wafer by dipping it in a solution containing a hydrophobic polymer. They then submerged the wafer in water, which wedged the layers off the silicon base. Intermolecular forces between the graphene and silicon provide a stable attachment and eliminate the need for glue, Dekker says. Repeating the technique several times would allow graphene layers to be built up into a complex nanoelectronic structure. “A [three-dimensional] microelectrode can be designed, layer by layer, using our ‘wedging’ transfer technique,” Schneider says.
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