Scalable Metadata-Hiding for Privacy-Preserving IoT Systems
Authors: Yunang Chen (University of Wisconsin-Madison), David Heath (University of Illinois Urbana-Champaign), Rahul Chatterjee (University of Wisconsin-Madison), Earlence Fernandes (University of California San Diego)
Volume: 2024
Issue: 4
Pages: 649–664
DOI: https://doi.org/10.56553/popets-2024-0135
Abstract: Modern cloud-based IoT services comprise an integrator service and several device vendor services. The vendor services enable users to remotely control their devices, while the integrator serves as a central intermediary, offering a unified interface for managing devices from different vendors. Although such a model is quite beneficial for IoT services to evolve quickly, it also creates a serious privacy concern: the vendor and integrator services observe all interactions between users and devices. Toward this, we propose Mohito, a privacy-preserving IoT system that hides such interactions from both the integrator and the vendors. In Mohito, we protect both the interaction data and the metadata, so that no one learns which user is communicating with which device. By utilizing oblivious key-value storage as a primitive and leveraging the unique communication graph of IoT services, we build a scalable protocol specialized in handling large concurrent traffic, a common demand in IoT systems. Our evaluation shows that Mohito can achieve up to 600x more throughput than the state-of-the-art general-purpose systems that provide similar security guarantees.
Keywords: Internet of Things, privacy, metadata protection, anonymous communication
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