Paper Info
Title
Peekaboo: A Hub-Based Approach to Enable Transparency in Data Processing within Smart Homes
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 preprocessing 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 privacy features to users across apps and devices, without additional effort from app developers. We present the design and implementation of Peekaboo, along with an evaluation of its coverage of smart home scenarios, system performance, data minimization, and example built-in privacy features.
Year
DOI
Venue
2022
10.1109/SP46214.2022.9833629
2022 IEEE Symposium on Security and Privacy (SP)
Keywords
DocType
ISSN
Data-minimization,Smart-Home,Privacy,Transparency
Conference
1081-6011
ISBN
Citations 
PageRank 
978-1-6654-1317-6
0
0.34
References 
Authors
31
6
Name
Order
Citations
PageRank
Haojian Jin14610.08
Gram Liu200.34
David Hwang300.34
Swarun Kumar439335.36
Yuvraj Agarwal51327102.62
Jason Hong66706518.75