학술논문

Aggregating Crowd Wisdom via Blockchain: A Private, Correct, and Robust Realization
Document Type
Conference
Source
2019 IEEE International Conference on Pervasive Computing and Communications (PerCom Pervasive Computing and Communications (PerCom), 2019 IEEE International Conference on. :1-10 Mar, 2019
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Geoscience
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Blockchain
Task analysis
Cryptography
Smart contracts
Differential privacy
Aggregates
Smart Contract
Crowdsensing
Data Confidentiality
Differential Privacy
Trusted Hardware
Zero-Knowledge Proof
Language
ISSN
2474-249X
Abstract
Crowdsensing, driven by the proliferation of sensor-rich mobile devices, has emerged as a promising data sensing and aggregation paradigm. Despite useful, traditional crowdsensing systems typically rely on a centralized third-party platform for data collection and processing, which leads to concerns like single point of failure and lack of operation transparency. Such centralization hinders the wide adoption of crowdsensing by wary participants. We therefore explore an alternative design space of building crowdsensing systems atop the emerging decentralized blockchain technology. While enjoying the benefits brought by the public blockchain, we endeavor to achieve a consolidated set of desirable security properties with a proper choreography of latest techniques and our customized designs. We allow data providers to safely contribute data to the transparent blockchain with the confidentiality guarantee on individual data and differential privacy on the aggregation result. Meanwhile, we ensure the service correctness of data aggregation and sanitization by delicately employing hardware-assisted transparent enclave. Furthermore, we maintain the robustness of our system against faulty data providers that submit invalid data, with a customized zero-knowledge range proof scheme. The experiment results demonstrate the high efficiency of our designs on both mobile client and SGX-enabled server, as well as reasonable on-chain monetary cost of running our task contract on Ethereum.