Deleting Data at Organizational Scale
Explore strategies for large-scale data deletion, addressing challenges of data sprawl, architectural complexity, and privacy rights while maintaining legitimate data usage in organizational settings.
Utility Analysis for Differentially-Private Pipelines
Explore a methodology for estimating differential privacy's impact on data quality, aiding informed decision-making in implementing privacy-preserving pipelines.
How We Can Save Anonymization - Principles for Effective Data Protection
Exploring effective data anonymization techniques to restore trust in privacy protection. Discusses operational principles for reliable anonymization methods, addressing past failures and skepticism.
Governing Identity Respectfully - User-Centric Approaches and Multistakeholder Governance
Exploring user-centric identity governance, balancing individual agency with ecosystem needs. Discusses multistakeholder approaches, lessons from past efforts, and privacy implications in identity systems.
Through the Lens of LLMs - Unveiling Differential Privacy Challenges
Explores LLMs as potential attackers in differential privacy, focusing on Google's Topics API vulnerabilities. Reveals increased re-identification risks and challenges privacy claims using practical simulations and LLM-driven analysis.
Cache-22: Doing Privacy Engineering with Privacy Standards
Explores privacy engineering practices through interviews, highlighting diverse responsibilities, use of standards, and organizational relationships. Reveals focus on legal compliance over policy development.
Don't End Up in the PETs Cemetery - Privacy Enhancing Technologies Spectrum
Explores Privacy Enhancing Technologies' spectrum, focusing on multi-party computation and private relays. Discusses FTC's stance and emphasizes accurate privacy claims for companies using PETs.
A New Model for International, Privacy-Preserving Data Science
Explore a groundbreaking approach to international data analysis using privacy-preserving technologies, enabling secure collaboration between statistical organizations without direct data access.
Empowered User Control: Learnings from Building Event Level Deletion
Explore Meta's new privacy initiative enabling users to delete ad interaction history, impacting data infrastructure and feature representation in Facebook's ad ranking system.
Consent Management at Airbnb - Building a Scalable Platform for GDPR Compliance
Explore Airbnb's Consent Management Platform, designed to address GDPR compliance and user privacy. Learn about its data model, API, and scalability for various consent scenarios.
Automating Technical Privacy Reviews Using LLMs
Exploring LLM automation for technical privacy reviews: efficiency gains, challenges, and limitations in agile environments. Insights from Uber and HERE Technologies on triage processes and AI integration.
FTC, Privacy, and You - Understanding the Federal Trade Commission's Role
Explore the FTC's role in privacy and technology, including its dual mandate, the new Office of Technology, and how privacy engineers support the agency's mission.
Designing a Data Subject Access Rights Tool
Exploring challenges in data subject access requests and proposing user-friendly solutions for better understanding and control of personal data collected by companies.
Approaches and Challenges to Purpose Limitation across Diverse Data Uses
Explore Meta's innovative solutions for purpose limitation in data privacy, addressing challenges of scale, granularity, and conditional flows through annotation-based policy checks.
Why "Safety"? How We Use Measurement to Advance Governance of Technology
Explore Internet Safety Labs' approach to software safety, including measurement methodologies, app safety labels, and data collection techniques for advancing technology governance.
Lessons Learned Deploying the Global Privacy Control to Millions of Customers
Insights on implementing Global Privacy Control at scale, covering standard overview, deployment challenges, and key learnings from Amazon's experience with millions of users.
Empirical Privacy Metrics in Synthetic Data Generation - The Bad, the Ugly, and the Good
Explore synthetic data generation, empirical privacy metrics, and their implications for data privacy. Uncover myths, assess usefulness, and learn requirements for effective privacy protection in data analysis and sharing.
Measuring Privacy Risks in Mobile Apps at Scale
Explore Internet Safety Labs' research on privacy risks in K-12 EdTech apps, including methodology, key findings, and challenges in large-scale privacy measurement.
Navigating the Privacy Landscape of AI on Devices - Challenges and Best Practices
Explore challenges and best practices for balancing AI advancements with user privacy on personal devices, focusing on responsible data handling and transparent AI development.
How Privacy Engineering Can Streamline the M&A Process
Explore how Privacy Engineering principles and advanced methodologies can streamline M&A processes, mitigate risks, and provide crucial insights during early acquisition stages.
Building a Protocol to Improve Data Subject Request Flexibility and Integration
Exploring a protocol for efficient data subject request handling, from intake to system-wide propagation. Discusses payload structures, implementation lessons, and future applications for improved DSR flexibility.