Engineering Commons^™

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams

USF Tampa Graduate Theses and Dissertations

This dissertation proposes a novel method called state-dependent sensor measurement models (SDSMMs). Such models dynamically predict the state-dependent bias and uncertainty of sensor measurements, ultimately improving fundamental robot tasks such as localization. In our first investigation, we introduced the state-dependent sensor measurement model framework, described their properties, stated the input and output of these models, and described how to train them. We also explained how to integrate such models with an Extended Kalman Filter and a Particle Filter, two popular robot state estimation algorithms. We validated the proposed framework through a series of localization tasks. The results showed that our …

Trilateration-Based Localization In Known Environments With Object Detection, Valeria M. Salas Pacheco

USF Tampa Graduate Theses and Dissertations

Many strategies for localization have been proposed, the majority of which rely on distance calculations and estimates. The proposed approach is a method that combines image-based single-camera localization techniques and the principle of trilateration to perform localization in a known indoor environment. By using a camera, the proposed system can detect custom objects using object detection in an indoor environment and calculate an approximation of the camera’s position. To recognize the location, previous information such as the size of the environment and the coordinates and sizes of the objects in the environment are given as input to the system together …

Enterprise Environment Modeling For Penetration Testing On The Openstack Virtualization Platform, Vincent Karovic Jr., Jakub Bartalos, Vincent Karovic, Michal Gregus

Journal of Global Business Insights

The article presents the design of a model environment for penetration testing of an organization using virtualization. The need for this model was based on the constantly increasing requirements for the security of information systems, both in legal terms and in accordance with international security standards. The model was created based on a specific team from the unnamed company. The virtual working environment offered the same functions as the physical environment. The virtual working environment was created in OpenStack and tested with a Linux distribution Kali Linux. We demonstrated that the virtual environment is functional and its security testable. Virtualizing …

Adaptive Mobile Eeg Noise Cancellation Using 2d Convolutional Autoencoders For Bci Authentication, Tyree Lewis

USF Tampa Graduate Theses and Dissertations

Electroencephalography (EEG) signals can be used for many purposes and has the potential to be adapted to various systems. When EEG is recorded from users, these studies are performed primarily in an indoor environment, while the user is stationary. This is due to the levels of noise that are experienced when recording EEG data, to minimize errors in the data. This thesis aims to adapt tasks that are performed indoors to an external environment by removing both noise and artefacts in EEG, using a 2D Convolutional Autoencoder (CAE). The data is recorded from subjects is passed into the 2D CAE …

Secure Vlsi Hardware Design Against Intellectual Property (Ip) Theft And Cryptographic Vulnerabilities, Matthew Dean Lewandowski

USF Tampa Graduate Theses and Dissertations

Over the last two decades or so, VLSI hardware is increasingly subject to sophisticated attacks on both the supply chain and design fronts. There is no explicit trust that the manufacturers/providers are not producing counterfeit designs or that cryptographic algorithms we know to be secure in software are also secure in hardware. The novelty and key contributions of this work are as follows: 1) a continually refined method for Intellectual Property (IP) Protection that provides an approach for verification of IP ownership, 2) demonstrate how to break the PRESENT-80 cryptographic algorithm with significantly limited resources, and 3) provide a multitude …

Data-Oriented Approaches Towards Mobile, Network And Secure Systems, Shangqing Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid evolvement of information science, data-oriented research has solicited a new philosophy for the future mobile network and security design, since it can not only encourage new designs achieving more efficient and reliable networks, but also pose new challenges towards security designs. In this dissertation, we propose four novel data-oriented designs or frameworks to prompt or calibrate the performance with respect to efficiency, reliability, and security.

In the wireless domain, packet corruption and packet collision are two major threats that jeopardize the performance of a mobile network. To cope with the packet corruption, we propose the STAteful inter-Packet …

Interrelation Of Thermal Stimulation With Haptic Perception, Emotion, And Memory, Mehdi Hojatmadani

USF Tampa Graduate Theses and Dissertations

Haptics is an interdisciplinary field of science that deals with how humans perceive and respond to different sensory cues perceived through touch. Thermal haptics as a branch deals with how humans perceive the temperature sensation and respond to that. The process in which thermal perception occurs is well known to researchers. What seems missing in the literature is how temperature interacts or sometimes intervenes in other physiological and psychological aspects of our lives. In this research, a series of studies are presented where the main focus was how temperature and brain interact with each other to impede or enhance our …

Data-Driven Studies On Social Networks: Privacy And Simulation, Yasanka Sameera Horawalavithana

USF Tampa Graduate Theses and Dissertations

Social media datasets are fundamental to understanding a variety of phenomena, such as epidemics, adoption of behavior, crowd management, and political uprisings. At the same time, many such datasets capturing computer-mediated social interactions are recorded nowadays by individual researchers or by organizations. However, while the need for real social graphs and the supply of such datasets are well established, the flow of data from data owners to researchers is significantly hampered by privacy risks: even when humans’ identities are removed, or data is anonymized to some extent, studies have proven repeatedly that re-identifying anonymized user identities (i.e., de-anonymization) is doable …

Analysis Of Denial Of Service Attacks In Emerging Software Defined Network Infrastructures, Andrea P. Wright

USF Tampa Graduate Theses and Dissertations

Software defined networking (SDN) improves upon traditional networking protocol technologies by decoupling the data and control planes and moving all control provisioning decisions to a centralized SDN controller entity. This concept has matured over the last decade, having gained strong industry traction, and is now being widely deployed within enterprise and carrier networks to streamline network services provisioning and reduce costs. Overall, centralized control delivers much more cost-effective and flexible networking setups that can support a wide range of customized user-driven network management applications, e.g., traffic engineering, security, survivability, admission control, policy control, etc.

However, the separation of the data …

Efficient Hardware Constructions For Error Detection Of Post-Quantum Cryptographic Schemes, Alvaro Cintas Canto

USF Tampa Graduate Theses and Dissertations

Quantum computers are presumed to be able to break nearly all public-key encryption algorithms used today. The National Institute of Standards and Technology (NIST) started the process of soliciting and standardizing one or more quantum computer resistant public-key cryptographic algorithms in late 2017. It is estimated that the current and last phase of the standardization process will last till 2022-2024. Among those candidates, code-based and multivariate-based cryptography are a promising solution for thwarting attacks based on quantum computers. Nevertheless, although code-based and multivariate-based cryptography, e.g., McEliece, Niederreiter, and Luov cryptosystems, have good error correction capabilities, research has shown their hardware …

Strategies In Botnet Detection And Privacy Preserving Machine Learning, Di Zhuang

USF Tampa Graduate Theses and Dissertations

Peer-to-peer (P2P) botnets have become one of the major threats in network security for serving as the infrastructure that responsible for various of cyber-crimes. Though a few existing work claimed to detect traditional botnets effectively, the problem of detecting P2P botnets involves more challenges. In this dissertation, we present two P2P botnet detection systems, PeerHunter and Enhanced PeerHunter. PeerHunter starts from a P2P hosts detection component. Then, it uses mutual contacts as the main feature to cluster bots into communities. Finally, it uses community behavior analysis to detect potential botnet communities and further identify bot candidates. Enhanced PeerHunter is an …

Pain Recognition Performance On A Single Board Computer, Iyonna L. Tynes

USF Tampa Graduate Theses and Dissertations

Emotion recognition is a quickly growing field of study due to the increased interest in building systems which can classify and respond to emotions. Recent medical crises, such as the opioid overdose epidemic in the United States and the global COVID-19 pandemic has emphasized the importance of emotion recognition applications is areas like Telehealth services. Considering this, this thesis focuses specifically on pain recognition. The problem of pain recognition is approached from both a hardware and software perspective, as we propose a real-time pain recognition system, from facial images, that is deployed on an NVIDIA Jetson Nano single-board computer. We …