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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!

2026

Venue Title Topic
ACM CAIS 2026 AgentStop: Terminating Local AI Agents Early to Save Energy in Consumer Devices LLM, Agents, Energy Efficiency
USENIX Security Efficient Threshold ML-DSA Security, Cryptography
IEEE S&P Coral: Fast Succinct Non-Interactive Zero-Knowledge CFG Proofs Security, Cryptography

2025

Venue Title Topic
NeurIPS Secure and Confidential Certificates of Online Fairness Fairness, ZKP
NeurIPS Pin the Tail on the Model: Blindfolded Repair of User-Flagged Failures in Text-to-Image Services Alignment, MPC
NDSS DiStefano: Decentralized Infrastructure for Sharing Trusted Encrypted Facts and Nothing More Security, Cryptography
CCS Nebula: Efficient, Private and Accurate Histogram Estimation Differential Privacy, Cryptography
EMNLP Membership and Memorization in LLM Knowledge Distillation Privacy, LLM
EMNLP Context-Aware Membership Inference Attacks against Pre-trained Large Language Models Privacy, LLM
ICML Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention Machine Learning, Cryptography
PETS TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks Privacy, Machine Learning
PETS Measuring the Accuracy and Effectiveness of PII Removal Services Privacy
CCS Local Frames: Exploiting Inherited Origins to Bypass Content Blockers Privacy
PQCrypto Share the MAYO: thresholdizing MAYO Security, Cryptography
USENIX Web Execution Bundles: Reproducible, Accurate, and Archivable Web Measurements Measurements, Privacy

2024

Venue Title Topic
MobiCom MELTing Point: Mobile Evaluation of Language Transformers Machine Learning, Systems
IMC A First Look at Related Website Sets Privacy
CCS Unbundle-Rewrite-Rebundle: Runtime Detection and Rewriting of Privacy-Harming Code in JavaScript Bundles Privacy
ICML Maestro: Uncovering Low-Rank Structures via Trainable Decomposition Machine Learning
ICML Recurrent Early Exits for Federated Learning with Heterogeneous Clients Machine Learning
ICLR Confidential-DPproof: Confidential Proof of Differentially Private Training Machine Learning
AfricaCrypt CDLS: Proving Knowledge of Committed Discrete Logarithms with Soundness Security, Cryptography
CCS Call Me By My Name: Simple, Practical Private Information Retrieval for Keyword Queries Security, Cryptography

2023

Venue Title Topic
IMC Understanding the Privacy Risks of Popular Search Engine Advertising Systems Privacy
IMC A First Look At The Privacy Harms Of The Public Suffix List Privacy
IEEE S&P Practically-exploitable Cryptographic Vulnerabilities in Matrix Security, Cryptography
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 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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