Securing Heterogeneous IoT systems

Over the past few years, the Internet of Things (IoT) has become an essential element of daily life. At the core of IoT are the densely deployed heterogeneous IoT sensors, such as RFID tags, cameras, temperature sensors, pressure sensors. These sensors work collectively to sense and capture intricate details of the surroundings, enabling the provision of highly detailed and comprehensive information. This fine-grained information encompasses a wide range of critical parameters that contribute to intelligent decision-making processes. Therefore, the security and privacy of heterogeneous IoT systems are indispensable. The heterogeneous nature of IoT systems poses a number of security and privacy challenges, including device security and privacy, data security and privacy, communication security, and AI and machine learning security. This dissertation delves into specific research issues related to device, communication, and data security, addressing them comprehensively. By focusing on these critical aspects, this work aims to enhance the security and privacy of heterogeneous IoT systems, contributing to their reliable and trustworthy operation. Specifically, Chapter 1 introduces the challenges and existing solutions in heterogeneous IoT systems. Chapter 2 presents SmartRFID, a novel UHF RFID authentication system to promote commodity crypto-less UHF RFID tags for security-sensitive applications. Chapter 3 presents WearRF-CLA, a novel CLA scheme built upon increasingly popular wrist wearables and UHF RFID systems. Chapter 4 presents the design and evaluation of PhyAuth, a PHY message authentication framework against packet-inject attacks in ZigBee networks. Chapter 5 presents NeighborWatch, a novel image-forgery detection framework for multi-cameras system with OFoV. Chapter 6 discusses the future work.