Hiding in Plain Sight: An IoT Traffic Camouflage Framework for Enhanced Privacy

This paper presents a practical traffic camouflage framework for reducing privacy leakage from encrypted IoT communications. The framework implements and evaluates six obfuscation mechanisms, including padding, padding with XORing, padding with shifting, constant-size padding, fragmentation, and delay randomization. By comparing their impact on learning-based traffic analysis and communication overhead, the study clarifies the privacy-performance trade-offs that shape deployable metadata protection for resource-constrained IoT environments.