Peekaboo: A Hub-Based Approach to Enable Transparency in Data Processing within Smart Homes (Extended Technical Report)
Haojian Jin, Gram Liu, David Hwang, Swarun Kumar, Yuvraj Agarwal,, Jason I. Hong

TL;DR
Peekaboo is a privacy-preserving architecture for smart homes that uses a hub to pre-process data with chainable operators, enabling explicit data collection policies and enhancing transparency and privacy.
Contribution
It introduces a hub-based system with a fixed set of operators and explicit developer declarations to improve privacy and transparency in smart home data processing.
Findings
Effective data minimization in smart home scenarios
System performance suitable for real-time processing
Enhanced transparency and privacy features implemented
Abstract
We present Peekaboo, a new privacy-sensitive architecture for smart homes that leverages an in-home hub to pre-process and minimize outgoing data in a structured and enforceable manner before sending it to external cloud servers. Peekaboo's key innovations are (1) abstracting common data pre-processing functionality into a small and fixed set of chainable operators, and (2) requiring that developers explicitly declare desired data collection behaviors (e.g., data granularity, destinations, conditions) in an application manifest, which also specifies how the operators are chained together. Given a manifest, Peekaboo assembles and executes a pre-processing pipeline using operators pre-loaded on the hub. In doing so, developers can collect smart home data on a need-to-know basis; third-party auditors can verify data collection behaviors; and the hub itself can offer a number of centralized…
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Taxonomy
TopicsContext-Aware Activity Recognition Systems · IoT and Edge/Fog Computing · Privacy-Preserving Technologies in Data
