Hsun Lee (National Taiwan University), Yuming Hsu (National Taiwan University), Jing-Jie Wang (National Taiwan University), Hao Cheng Yang (National Taiwan University), Yu-Heng Chen (National Taiwan University), Yih-Chun Hu (University of Illinois at Urbana-Champaign), Hsu-Chun Hsiao (National Taiwan University)

Generating randomness by public participation allows participants to contribute randomness directly and verify the result's security. Ideally, the difficulty of participating in such activities should be as low as possible to reduce the computational burden of being a contributor. However, existing randomness generation protocols are unsuitable for this scenario because of scalability or usability issues. Hence, in this paper we present HeadStart, a participatory randomness protocol designed for public participation at scale. HeadStart allows contributors to verify the result on commodity devices efficiently, and provides a parameter $L$ that can make the result-publication latency $L$ times lower. Additionally, we propose two implementation improvements to speed up the verification further and reduce the proof size. The verification complexity of HeadStart is only $O(L times polylog(T) +log C)$ for a contribution phase lasting for time $T$ with $C$ contributions.

View More Papers

D-Box: DMA-enabled Compartmentalization for Embedded Applications

Alejandro Mera (Northeastern University), Yi Hui Chen (Northeastern University), Ruimin Sun (Northeastern University), Engin Kirda (Northeastern University), Long Lu (Northeastern University)

Read More

Vehicle Lateral Motion Stability Under Wheel Lockup Attacks

Alireza Mohammadi (University of Michigan-Dearborn) and Hafiz Malik (University of Michigan-Dearborn)

Read More

Generating Test Suites for GPU Instruction Sets through Mutation...

Shoham Shitrit(University of Rochester) and Sreepathi Pai (University of Rochester)

Read More

The Inconvenient Truths of Ground Truth for Binary Analysis

Jim Alves-Foss, Varsha Venugopal (University of Idaho)

Read More