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Articles 1 - 7 of 7
Full-Text Articles in Other Computer Engineering
Towards Secure Deep Neural Networks For Cyber-Physical Systems, Jiangnan Li
Towards Secure Deep Neural Networks For Cyber-Physical Systems, Jiangnan Li
Doctoral Dissertations
In recent years, deep neural networks (DNNs) are increasingly investigated in the literature to be employed in cyber-physical systems (CPSs). DNNs own inherent advantages in complex pattern identifying and achieve state-of-the-art performances in many important CPS applications. However, DNN-based systems usually require large datasets for model training, which introduces new data management issues. Meanwhile, research in the computer vision domain demonstrated that the DNNs are highly vulnerable to adversarial examples. Therefore, the security risks of employing DNNs in CPSs applications are of concern.
In this dissertation, we study the security of employing DNNs in CPSs from both the data domain …
Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan
Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan
Doctoral Dissertations
This dissertation addresses the components necessary for simulation of an image-based recovery of the position of a target using orbital image sensors. Each component is considered in detail, focusing on the effect that design choices and system parameters have on the accuracy of the position estimate. Changes in sensor resolution, varying amounts of blur, differences in image noise level, selection of algorithms used for each component, and lag introduced by excessive processing time all contribute to the accuracy of the result regarding recovery of target coordinates using orbital sensor data.
Using physical targets and sensors in this scenario would be …
Wide-Area Measurement-Driven Approaches For Power System Modeling And Analytics, Hesen Liu
Wide-Area Measurement-Driven Approaches For Power System Modeling And Analytics, Hesen Liu
Doctoral Dissertations
This dissertation presents wide-area measurement-driven approaches for power system modeling and analytics. Accurate power system dynamic models are the very basis of power system analysis, control, and operation. Meanwhile, phasor measurement data provide first-hand knowledge of power system dynamic behaviors. The idea of building out innovative applications with synchrophasor data is promising.
Taking advantage of the real-time wide-area measurements, one of phasor measurements’ novel applications is to develop a synchrophasor-based auto-regressive with exogenous inputs (ARX) model that can be updated online to estimate or predict system dynamic responses.
Furthermore, since auto-regressive models are in a big family, the ARX model …
Compressed Sensing In Resource-Constrained Environments: From Sensing Mechanism Design To Recovery Algorithms, Shuangjiang Li
Compressed Sensing In Resource-Constrained Environments: From Sensing Mechanism Design To Recovery Algorithms, Shuangjiang Li
Doctoral Dissertations
Compressed Sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. It is promising that CS can be utilized in environments where the signal acquisition process is extremely difficult or costly, e.g., a resource-constrained environment like the smartphone platform, or a band-limited environment like visual sensor network (VSNs). There are several challenges to perform sensing due to the characteristic of these platforms, including, for example, needing active user involvement, computational and storage limitations and lower transmission capabilities. This dissertation focuses on the study of …
Statistical Analysis Of Disturbances In Power Transmission Systems, Liu Liu
Statistical Analysis Of Disturbances In Power Transmission Systems, Liu Liu
Masters Theses
Disturbance analysis is essential to the study of the power transmission systems. Traditionally, disturbances are described as megawatt (MW) events, but the access to data is inefficient due to the slow installation and authorization process of the monitoring device. In this paper, we propose a novel approach to disturbance analysis conducted at the distribution level by exploiting the frequency recordings from Frequency Disturbance Recorders (FDRs) of the Frequency Monitoring Network (FNET/GridEye), based on the relationship between frequency change and the power loss of disturbances - linearly associated by the Frequency Response. We first analyze the real disturbance records of North …
Improved Forensic Medical Device Security Through Eating Detection, Nathan Lee Henry
Improved Forensic Medical Device Security Through Eating Detection, Nathan Lee Henry
Masters Theses
Patients are increasingly reliant on implantable medical device systems today. For patients with diabetes, an implantable insulin pump system or artificial pancreas can greatly improve quality of life. As with any device, these devices can and do suffer from software and hardware issues, often reported as a safety event. For a forensic investigator, a safety event is indistinguishable from a potential security event. In this thesis, we show a new sensor system that can be transparently integrated into existing and future electronic diabetes therapy systems while providing additional forensic data to help distinguish between safety and security events. We demonstrate …
Collaborative Solutions To Visual Sensor Networks, Mahmut Karakaya
Collaborative Solutions To Visual Sensor Networks, Mahmut Karakaya
Doctoral Dissertations
Visual sensor networks (VSNs) merge computer vision, image processing and wireless sensor network disciplines to solve problems in multi-camera applications in large surveillance areas. Although potentially powerful, VSNs also present unique challenges that could hinder their practical deployment because of the unique camera features including the extremely higher data rate, the directional sensing characteristics, and the existence of visual occlusions.
In this dissertation, we first present a collaborative approach for target localization in VSNs. Traditionally; the problem is solved by localizing targets at the intersections of the back-projected 2D cones of each target. However, the existence of visual occlusions among …