Security and privacy in fog computing is a critical research area that addresses the unique challenges posed by distributed, heterogeneous, and resource-constrained fog environments. Unlike centralized cloud infrastructures, fog nodes are often deployed closer to end-users and IoT devices, making them more vulnerable to cyberattacks, data breaches, and malicious tampering. Research papers in this field explore lightweight cryptographic protocols, secure authentication and authorization mechanisms, intrusion detection systems, and blockchain-based frameworks to safeguard fog infrastructures. Studies emphasize privacy-preserving computation techniques such as homomorphic encryption, differential privacy, and federated learning to protect sensitive user and IoT data while enabling efficient processing at the edge. Recent works investigate trust management, anomaly detection, and access control frameworks that are adaptive, context-aware, and scalable across multi-tier fog–edge–cloud ecosystems. Multi-objective optimization models balancing security with performance, energy efficiency, and Quality of Service (QoS) are also being developed. Applications include healthcare monitoring, autonomous vehicles, industrial IoT, and smart cities, where both data confidentiality and system reliability are paramount. Overall, research in security and privacy for fog computing ensures resilient, trustworthy, and sustainable infrastructures, supporting the safe adoption of latency-sensitive and mission-critical services in next-generation distributed computing.