Bingsheng Zhang (Lancaster University), Roman Oliynykov (IOHK Ltd.), Hamed Balogun (Lancaster University)

A treasury system is a community-controlled and decentralized collaborative decision-making mechanism for sustainable funding of blockchain development and maintenance. During each treasury period, project proposals are submitted, discussed, and voted for; top-ranked projects are funded from the treasury. The Dash governance system is a real-world example of such kind of systems. In this work, we, for the first time, provide a rigorous study of the treasury system. We modelled, designed, and implemented a provably secure treasury system that is compatible with most existing blockchain infrastructures, such as Bitcoin, Ethereum, etc. More specifically, the proposed treasury system supports liquid democracy/delegative voting for better collaborative intelligence. Namely, the stake holders can either vote directly on the proposed projects or delegate their votes to experts. Its core component is a distributed universally composable secure end-to-end verifiable voting protocol. The integrity of the treasury voting decisions is guaranteed even when all the voting committee members are corrupted. To further improve efficiency, we proposed the world’s first honest verifier zero-knowledge proof for unit vector encryption with logarithmic size communication. This partial result may be of independent interest to other cryptographic protocols. A pilot system is implemented in Scala over the Scorex 2.0 framework, and its benchmark results indicate that the proposed system can support tens of thousands of treasury participants with high efficiency.

View More Papers

Profit: Detecting and Quantifying Side Channels in Networked Applications

Nicolás Rosner (University of California, Santa Barbara), Ismet Burak Kadron (University of California, Santa Barbara), Lucas Bang (Harvey Mudd College), Tevfik Bultan (University of California, Santa Barbara)

Read More

Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation

Victor Le Pochat (imec-DistriNet, KU Leuven), Tom Van Goethem (imec-DistriNet, KU Leuven), Samaneh Tajalizadehkhoob (Delft University of Technology), Maciej Korczyński (Grenoble Alps University), Wouter Joosen (imec-DistriNet, KU Leuven)

Read More

Geo-locating Drivers: A Study of Sensitive Data Leakage in...

Qingchuan Zhao (The Ohio State University), Chaoshun Zuo (The Ohio State University), Giancarlo Pellegrino (CISPA, Saarland University; Stanford University), Zhiqiang Lin (The Ohio State University)

Read More

Nearby Threats: Reversing, Analyzing, and Attacking Google’s ‘Nearby Connections’...

Daniele Antonioli (Singapore University of Technology and Design (SUTD)), Nils Ole Tippenhauer (CISPA), Kasper Rasmussen (University of Oxford)

Read More