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.

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Demo #14: In-Vehicle Communication Using Named Data Networking

Zachariah Threet (Tennessee Tech), Christos Papadopoulos (University of Memphis), Proyash Poddar (Florida International University), Alex Afanasyev (Florida International University), William Lambert (Tennessee Tech), Haley Burnell (Tennessee Tech), Sheikh Ghafoor (Tennessee Tech) and Susmit Shannigrahi (Tennessee Tech)

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FANDEMIC: Firmware Attack Construction and Deployment on Power Management...

Ryan Tsang (University of California, Davis), Doreen Joseph (University of California, Davis), Qiushi Wu (University of California, Davis), Soheil Salehi (University of California, Davis), Nadir Carreon (University of Arizona), Prasant Mohapatra (University of California, Davis), Houman Homayoun (University of California, Davis)

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Building the VPNalyzer System

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue, Roya Ensafi (University of Michigan)

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