Privacy-Preserving Techniques in Cloud/Fog and Internet of Things.

This document is a summary of a special issue on privacy-preserving techniques in cloud/fog and Internet of Things (IoT) networks. The issue explores various methods and strategies for protecting privacy in these networks, including cryptographic algorithms, federated learning models, and password-less authentication. The authors also discuss the challenges of securing IoT devices with limited computational power and the importance of safeguarding data in large networks. The special issue includes 10 selected papers out of a total of 21 submissions, covering topics such as true random number generation, shared key generation, watermarking, dependability assessment, authentication schemes, federated learning, batch processing, stylometry, and searchable encryption. The authors express their gratitude to the contributors for their valuable research in this field. [Extracted from the article]