Dragoon: Private decentralized hits made practical
Document Type
Conference Proceeding
Publication Date
11-1-2020
Abstract
—With the rapid popularity of blockchain, decentralized human intelligence tasks (HITs) are proposed to crowdsource human knowledge without relying on vulnerable third-party platforms. However, the inherent limits of blockchain cause decentralized HITs to face a few “new” challenges. For example, the confidentiality of solicited data turns out to be the sine qua non, though it was an arguably dispensable property in the centralized setting. To ensure the “new” requirement of data privacy, existing decentralized HITs use generic zero-knowledge proof frameworks (e.g., SNARK), but scarcely perform well in practice, due to the inherently expensive cost of generality. We present a practical decentralized protocol for HITs, which also achieves the fairness between requesters and workers. At the core of our contributions, we avoid the powerful yet highly-costly generic zk-proof tools and propose a special-purpose scheme to prove the quality of encrypted data. By various nontrivial statement reformations, proving the quality of encrypted data is reduced to efficient verifiable decryption, thus making decentralized HITs practical. Along the way, we rigorously define the ideal functionality of decentralized HITs and then prove the security due to the ideal/real paradigm. We further instantiate our protocol to implement a system called Dragoon1, an instance of which is deployed atop Ethereum to facilitate an image annotation task used by ImageNet. Our evaluations demonstrate its practicality: the on-chain handling cost of Dragoon is even less than the handling fee of Amazon’s Mechanical Turk for the same ImageNet HIT.
Identifier
85101859835 (Scopus)
ISBN
[9781728170022]
Publication Title
Proceedings International Conference on Distributed Computing Systems
External Full Text Location
https://doi.org/10.1109/ICDCS47774.2020.00084
First Page
910
Last Page
920
Volume
2020-November
Recommended Citation
Lu, Yuan; Tang, Qiang; and Wang, Guiling, "Dragoon: Private decentralized hits made practical" (2020). Faculty Publications. 4860.
https://digitalcommons.njit.edu/fac_pubs/4860
