Index Catalog // ScholarsArchive@OSU

On the domain generalizability of RF fingerprints through multifractal dimension representation

Creator:: Johnson, Benjamin
Abstract:: RF data-driven device fingerprinting through the use of deep learning has recently surfaced as a possible method for secure device identification and authentication. Traditional approaches are commonly susceptible to the domain adaptation problem where a model trained on data from one domain performs badly when tested on data from a...
Resource Type:: Masters Thesis
Full Text:: RF transmissions. 36 Bibliography [1] J. Zhang, S. Rajendran, Z. Sun, R

Towards Deep Learning Model Portability for Domain-Agnostic Device Fingerprinting

Creator:: Gaskin, Jared
Abstract:: In recent years, RF (Radio Frequency) device fingerprinting using deep learning has emerged as a method of identifying devices solely by their RF transmissions. Conventional approaches to this type of device fingerprinting are not portable to different domains. That is, if a model for this purpose is trained on data...
Resource Type:: Masters Thesis
Full Text:: : Bechir Hamdaoui Lizhong Chen In recent years, RF (Radio Frequency) device fingerprinting using deep

Leveraging Multiple Transmissions and Receptions for Channel-Agnostic Wireless Device Identification

Creator:: Basha, Nora
Abstract:: Enabling accurate and automated identification of wireless devices is critical for ensuring secure and authenticated data communication in large-scale networks such as IoT networks. In the aim of devising practical identification techniques that are immune to spoofing, hardware-driven RF fingerprinting using deep neural networks, which leverages the inevitable presence of...
Resource Type:: Masters Thesis

Leveraging Hardware-Impaired Out-of-Band Information Through Deep Neural Networks for Robust Wireless Device Classification

Creator:: Elmaghbub, Abdurrahman A.
Abstract:: Wireless device classification techniques play a key role in promoting emerging wireless applications such as allowing spectrum regulatory agencies to enforce their access policies and enabling network administrators to control access and prevent impersonation attacks to their wireless networks. Leveraging spectrum distortions of transmitted RF signals, caused by transceiver hardware...
Resource Type:: Masters Thesis
Full Text:: to the rest of my defense committee: Dr. Arun Natarajan, Dr. Lizhong Chen, Dr. Rakesh Bobba, and Dr

Towards Long Short Term Memory Based Proactive In-Network Caching for Cloud RANs

Creator:: Tirupathi, Chittibabu
Abstract:: The rapid population growth in large urban cities has led to an unprecedented increase in both the number and the diversity of wireless devices and applications with varying quality of service requirements in terms of latency and data rates. LinkNYC is an example of an urban communication network infrastructure, which...
Resource Type:: Masters Thesis

Location Privacy-Preserving Strategies for Secondary Spectrum Use

Creator:: Grissa, Mohamed
Abstract:: The scarcity of wireless spectrum resources and the overwhelming demand for wireless broadband resources have prompted industry, government agencies and academia within the wireless communities to develop and come up with effective solutions that can make additional spectrum available for broadband data. As part of these ongoing efforts, cognitive radio...
Resource Type:: Dissertation
Full Text:: committee members Professor Mag- gie Niess, Professor Lizhong Chen and Professor Mike Rosulek, for

Efficient Spectrum Sensing and Sharing Techniques for Dynamic Wideband Spectrum Access

Creator:: Khalfi, Bassem
Abstract:: Besides enabling an enhanced mobile broadband access, fifth-generation (5G) wireless mobile networks are envisioned to support the connectivity of massive, heterogeneous Internet of Things (IoT) devices. Connecting these devices through 5G systems and providing them with their needed data rates require huge amounts of spectrum and power resources, thus calling...
Resource Type:: Dissertation
Full Text:: Prof. Lizhong Chen for their insightful comments and encouragement. Also, I would like to thank my

Architectures and algorithms for dynamic overlay networks

Creator:: Abdelwahab, Sherif
Abstract:: Most of today’s Internet of Things (IoT) applications assume that data will be moved offdevices into centralized cloud platforms. While existing IoT systems leverage cloud-based analytics for meaningful data reasoning, the assumption that data should always be moved off the devices is problematic. The amount of data to be moved...
Resource Type:: Dissertation

Energy-Efficient Resource Management Techniques for Cloud Data Centers

Creator:: Dabbagh, Mehiar
Abstract:: Energy consumption has become a great deal for cloud service providers due to financial as well as environmental concerns. Studies show that cloud servers operate, most of the time, at only between 10% and 50% of their maximal utilizations. These same studies also show that servers that are kept ON...
Resource Type:: Dissertation

Leveraging Compressive Sampling and Machine Learning for Adaptive and Cooperative Wideband Spectrum Sensing

Creator:: Zaid, Adem
Abstract:: This thesis proposes a novel technique that exploits spectrum occupancy behaviors inherent to wideband spectrum access to enable efficient cooperative spectrum sensing. The proposed technique reduces the number of required sensing measurements while accurately recovering spectrum occupancy information. It does so by leveraging compressive sampling theory to exploit the block-like...
Resource Type:: Masters Thesis
Full Text:: 1–7. IEEE, 2015. [4] F. Azmat, Y. Chen, and N. Stocks. Analysis of spectrum occupancy using machine

ScholarsArchive@OSU

On the domain generalizability of RF fingerprints through multifractal dimension representation

Towards Deep Learning Model Portability for Domain-Agnostic Device Fingerprinting

Leveraging Multiple Transmissions and Receptions for Channel-Agnostic Wireless Device Identification

Leveraging Hardware-Impaired Out-of-Band Information Through Deep Neural Networks for Robust Wireless Device Classification

Towards Long Short Term Memory Based Proactive In-Network Caching for Cloud RANs

Location Privacy-Preserving Strategies for Secondary Spectrum Use

Efficient Spectrum Sensing and Sharing Techniques for Dynamic Wideband Spectrum Access

Architectures and algorithms for dynamic overlay networks

Energy-Efficient Resource Management Techniques for Cloud Data Centers

Leveraging Compressive Sampling and Machine Learning for Adaptive and Cooperative Wideband Spectrum Sensing

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