A Developer-Friendly Library for Smart Home IoT Privacy-Preserving Traffic Obfuscation

TL;DR

This paper introduces a Python library that simplifies the integration of privacy-preserving traffic obfuscation for IoT devices, effectively protecting user privacy with minimal bandwidth overhead.

Contribution

A developer-friendly Python library that automates traffic obfuscation for IoT devices, reducing implementation effort and bandwidth costs compared to existing solutions.

Findings

Successfully preserves user privacy against traffic analysis.

Requires approximately 4 KB/s overhead bandwidth for low-rate IoT devices.

Outperforms existing solutions in bandwidth efficiency.

Abstract

The number and variety of Internet-connected devices have grown enormously in the past few years, presenting new challenges to security and privacy. Research has shown that network adversaries can use traffic rate metadata from consumer IoT devices to infer sensitive user activities. Shaping traffic flows to fit distributions independent of user activities can protect privacy, but this approach has seen little adoption due to required developer effort and overhead bandwidth costs. Here, we present a Python library for IoT developers to easily integrate privacy-preserving traffic shaping into their products. The library replaces standard networking functions with versions that automatically obfuscate device traffic patterns through a combination of payload padding, fragmentation, and randomized cover traffic. Our library successfully preserves user privacy and requires approximately 4 KB/s overhead bandwidth for IoT devices with low send rates or high latency tolerances. This overhead is reasonable given normal Internet speeds in American homes and is an improvement on the bandwidth requirements of existing solutions.