GPS Anomaly Detection And Machine Learning Models For Precise Unmanned Aerial Systems

The rapid development and deployment of 5G/6G networks have brought numerous benefits such as faster speeds, enhanced capacity, improved reliability, lower latency, greater network efficiency, and enablement of new applications. Emerging applications of 5G impacting billions of devices and embedded electronics also pose cyber security vulnerabilities. This thesis focuses on the development of Global Positioning Systems (GPS) Based Anomaly Detection and corresponding algorithms for Unmanned Aerial Systems (UAS). Chapter 1 provides an overview of the thesis background and its objectives. Chapter 2 presents an overview of the 5G architectures, their advantages, and potential cyber threat types. Chapter 3 addresses the issue of GPS dropouts by taking the use case of the Dallas-Fort Worth (DFW) airport. By analyzing data from surveillance drones in the (DFW) area, its message frequency, and statistics on time differences between GPS messages were examined. Chapter 4 focuses on modeling and detecting false data injection (FDI) on GPS. Specifically, three scenarios, including Gaussian noise injection, data duplication, data manipulation are modeled. Further, multiple detection schemes that are Clustering-based and reinforcement learning techniques are deployed and detection accuracy were investigated. Chapter 5 shows the results of Chapters 3 and 4. Overall, this research provides a categorization and possible outlier detection to minimize the GPS interference for UAS enhancing the security and reliability of UAS operations

Internet of Things 2.0: Concepts, Applications, and Future Directions

Applications and technologies of the Internet of Things are in high demand with the increase of network devices. With the development of technologies such as 5G, machine learning, edge computing, and Industry 4.0, the Internet of Things has evolved. This survey article discusses the evolution of the Internet of Things and presents the vision for Internet of Things 2.0. The Internet of Things 2.0 development is discussed across seven major fields. These fields are machine learning intelligence, mission critical communication, scalability, energy harvesting-based energy sustainability, interoperability, user friendly IoT, and security. Other than these major fields, the architectural development of the Internet of Things and major types of applications are also reviewed. Finally, this article ends with the vision and current limitations of the Internet of Things in future network environments

Wireless communication, sensing, and REM: A security perspective

The diverse requirements of next-generation communication systems necessitate awareness, flexibility, and intelligence as essential building blocks of future wireless networks. The awareness can be obtained from the radio signals in the environment using wireless sensing and radio environment mapping (REM) methods. This is, however, accompanied by threats such as eavesdropping, manipulation, and disruption posed by malicious attackers. To this end, this work analyzes the wireless sensing and radio environment awareness mechanisms, highlighting their vulnerabilities and provides solutions for mitigating them. As an example, the different threats to REM and its consequences in a vehicular communication scenario are described. Furthermore, the use of REM for securing communications is discussed and future directions regarding sensing/REM security are highlighted