IoT Traffic Camouflage Framework Developed for User Privacy
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🕵️♂️ New IoT Traffic Camouflage Framework Enhances User Privacy. A novel multi-technique obfuscation framework has been developed to address privacy concerns arising from the Internet of Things (IoT) devices, which are vulnerable to traffic analysis despite encryption. The framework employs six techniques—Padding, Padding with XORing, Padding with Shifting, Constant Size Padding, Fragmentation, and Delay Randomization—to effectively obscure traffic patterns. Evaluations on public datasets indicate a significant decrease in the performance of machine learning classifiers, demonstrating the framework’s effectiveness against adaptive attacks. While higher levels of obfuscation improve privacy, they may also lead to increased latency and communication overhead, highlighting a trade-off between privacy and system performance.
