Physical Sciences and Mathematics Commons^™

Black Networks In Smart Cities, Shaibal Chakrabarty

Computer Science and Engineering Theses and Dissertations

In this dissertation, we present the Black Networks solution to protect both the data and the metadata for mobile ad-hoc Internet of Things (IoT) networks in Smart Cities. IoT networks are gaining popularity with billions of deployed nodes, and increasingly carrying mission-critical data, whose compromise can lead to catastrophic consequences. IoT nodes are resource-constrained and often exist within insecure environments, making them vulnerable to a broad range of active and passive attacks. Black IoT networks are designed to mitigate multiple communication-based attacks by encrypting the data and the metadata, within a communication frame or packet, while remaining compatible with the …

Cloud Service Reliability And Usability Measurement, Abdullah Bokhary

Computer Science and Engineering Theses and Dissertations

Cloud computing has become a major resource for fulfilling people's computational and storage needs. Investing in these services requires measuring and assuring its quality in general, and reliability and usability are primary concerns. However, using traditional reliability models can be challenging because of the environmental constraints and limited data availability due to the heterogeneous environment and diverse stakeholders. Also, the quality of cloud service Application Programming Interfaces (APIs) has a direct impact on the usability and reliability of the service.

We developed a framework to measure reliability with alternative available information that most cloud providers offer in three stages: 1) …

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …