Emily Stark

Over the past decade, HTTPS adoption has risen dramatically. The Web PKI has shifted seismically, with browsers imposing new requirements on CAs and server operators. These shifts bring security and privacy improvements for end users, but they have often been driven by incompatible browser changes that break websites, causing frustration for end users as well as server operators. Security-positive breaking changes involve a plethora of choices. Should browsers roll out a change gradually, or rip the band-aid off and deploy it all at once? How do we advertise the change and motivate different players in the ecosystem to update configurations before they break? How do different types and amounts of breakage affect the user experience? And the meta-question: how do we approach such quandaries scientifically? Drawing from several case studies in the HTTPS ecosystem, I'll talk about the science of nudging an ecosystem: methods that the web browser community has developed, and lessons we've learned, for measuring how best to get millions of websites to improve security while minimizing the frustrations of incompatibility.

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Understanding the Growth and Security Considerations of ECS

Athanasios Kountouras (Georgia Institute of Technology), Panagiotis Kintis (Georgia Institute of Technology), Athanasios Avgetidis (Georgia Institute of Technology), Thomas Papastergiou (Georgia Institute of Technology), Charles Lever (Georgia Institute of Technology), Michalis Polychronakis (Stony Brook University), Manos Antonakakis (Georgia Institute of Technology)

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LaKSA: A Probabilistic Proof-of-Stake Protocol

Daniel Reijsbergen (Singapore University of Technology and Design), Pawel Szalachowski (Singapore University of Technology and Design), Junming Ke (University of Tartu), Zengpeng Li (Singapore University of Technology and Design), Jianying Zhou (Singapore University of Technology and Design)

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K-resolver: Towards Decentralizing Encrypted DNS Resolution

N.P. Hoang, I. Lin, S. Ghavamnia, M. Polychronakis

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NetPlier: Probabilistic Network Protocol Reverse Engineering from Message Traces

Yapeng Ye (Purdue University), Zhuo Zhang (Purdue University), Fei Wang (Purdue University), Xiangyu Zhang (Purdue University), Dongyan Xu (Purdue University)

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