IoT is a network of interconnected devices that can communicate with and transfer data between each other. Fog computing creates a mid-layer between the network edge and the cloud to bring computing resources closer to the network edge. This results in faster data processing and lower latency. The present work explores the security and privacy of the rapidly proliferating IoT devices, which are becoming integral to everyday life. The landscape of key exchange, authentication, and session key establishment for IoT will then be discussed in depth, as well as alternative approaches. Quantum Guard: A Quantum-Resistant Security Framework for IoT Devices (QR-SFID) based on the PUF-based key exchange can be much more secure than classical key exchange methods to overcome the existing limitations. Moreover, it illustrates the many challenges in implementing secure RFID, which is critical to many healthcare IoT devices and implementing anonymity-preserving user authentication. Finally, this work explores how deep learning can enable widely deployable anomaly detection in IoT devices in this comprehensive, practical, theoretical solution to deploying secure, privacy-conscious IoT devices. By comparing several security approaches, the QR-SFID proposal is an invaluable resource for researchers and practitioners to select from the best security solutions that aptly secure IoT networks and devices.