Enhancing Smart Home Privacy: A Tutorial on Local Differential Privacy Techniques for Frequency and Mean Estimation

Journal Article · Wed Mar 12 00:00:00 EDT 2025 · IEEE Communications Magazine

DOI:https://doi.org/10.1109/MCOM.002.2400279· OSTI ID:3002906

Kotevska, Olivera ^[1]; He, Xi ^[2]; Al-Masri, Eyhab ^[3]

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1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
2. Univ. of Waterloo, ON (Canada)
3. Univ. of Washington, Tacoma, WA (United States)

The ubiquity of Internet of Things (IoT) systems has seamlessly integrated into our daily lives, particularly in smart homes where devices continuously monitor and optimize our living environments. These systems significantly contribute to home automation, energy efficiency, and overall comfort. However, this widespread connectivity poses inherent risks linked to the streaming of sensitive household data, necessitating robust privacy preservation mechanisms. This tutorial systematically examines privacy preservation through local differential privacy (LDP), with a particular focus on frequency and mean estimation techniques for smart home applications. Here, we present a comprehensive taxonomy of smart home data formats and provide detailed implementation guidance for event-based and w-event LDP mechanisms. Through practical examples using smart thermostats and HVAC systems, we demonstrate how these techniques can be effectively deployed in real-world scenarios. The tutorial concludes by examining emerging research directions, including adaptive privacy budgets and federated learning approaches, establishing a foundation for privacy-preserving smart home deployments.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 3002906
• Journal Information: IEEE Communications Magazine, Journal Name: IEEE Communications Magazine Journal Issue: 8 Vol. 63; ISSN 1558-1896; ISSN 0163-6804
• Publisher: IEEE
• Country of Publication: United States
• Language: English