Research at Brave

Papers

We are the Brave Research team! We work at the intersection of theory and practice on many topics in Computer Science. Our research mainly focuses on privacy, security, machine-learning, networks, and measurements. Read our work here!

2023

Venue	Title	Topic
PETS	FrodoPIR: Simple, Scalable, Single-Server Private Information Retrieval	Cryptography, Privacy
USENIX Security	Pool-Party: Exploiting Browser Resource Pools for Web Tracking	Privacy

2022

Venue	Title	Topic
HotNets	Tango or Square Dance? How Tightly Should we Integrate Network Functionality in Browsers?	Networks
IMC	Measuring UID Smuggling in the Wild	Privacy
CCS	STAR: Secret Sharing for Private Threshold Aggregation Reporting	Cryptography, Privacy
eprint	A Framework for Building Secure, Scalable, Networked Enclaves	Networks, Privacy
PETS	Blocked or Broken? Automatically Detecting When Privacy Interventions Break Websites	Privacy
PAM	BatteryLab: A Collaborative Platform for Power Monitoring	Measurements
WWW	Measuring the Privacy vs. Compatibility Trade-off in Preventing Third-Party Stateful Tracking	Privacy

2021

Venue	Title	Topic
CCS	SugarCoat: Programmatically Generating Privacy-Preserving, Web-Compatible Resource Replacements for Content Blocking	Privacy
eprint	PrivateFetch: Scalable Catalog Delivery in Privacy-Preserving Advertising	Cryptography
eprint	What's in Your Wallet? Privacy and Security Issues in Web 3.0	Privacy, Security, Measurements
PETS	zkSENSE: A Friction-less Privacy-Preserving Human Attestation Mechanism for Mobile Devices	Cryptography, Privacy
RecSys	Stronger Privacy for Federated Collaborative Filtering With Implicit Feedback	Machine Learning, Privacy
IEEE S&P	Detecting Filter List Evasion With Event-Loop-Turn Granularity JavaScript Signatures	Security
WWW	Towards Realistic and Reproducible Web Crawl Measurements	Measurements

2020

Venue	Title	Topic
CoNEXT	Mind the Delay: The Adverse Effects of Delay-Based TCP on HTTP	Networks
eprint	There's No Trick, Its Just a Simple Trick: A Web-Compat and Privacy Improving Approach to Third-Party Web Storage	Privacy
USENIX ATC	Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning	Machine Learning, Privacy
SIGMETRICS	Who Filters the Filters: Understanding the Growth, Usefulness and Efficiency of Crowdsourced Ad Blocking	Machine Learning, Privacy
IEEE S&P	AdGraph: A Machine Learning Approach to Automatic and Effective Adblocking	Machine Learning, Privacy
MLSys	Privacy-Preserving Bandits	Machine Learning, Privacy
WWW	Keeping Out the Masses: Understanding the Popularity and Implications of Internet Paywalls	Privacy
WWW	Filter List Generation for Underserved Regions	Privacy
CHI	Evaluating the End-User Experience of Private Browsing Mode	Machine Learning, Privacy
WWW	De-Kodi: Understanding the Kodi Ecosystem	Privacy

2019

Venue	Title	Topic
WWW	SpeedReader: Reader Mode Made Fast and Private	Privacy
HotNets	BatteryLab: A Distributed Platform for Battery Measurements	Measurements
eprint	The Blind Men and the Internet: Multi-Vantage Point Web Measurements	Privacy

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