The Promise of Differential Privacy
Explore differential privacy's role in addressing false discoveries and privacy risks in big data analysis. Learn theoretical foundations and practical applications.
Defending Against Cell Site Simulators (IMSI Catchers) - DragonCon 2024
Explore IMSI catchers, their use by law enforcement and criminals, and learn detection and defense strategies for mobile technology users.
Data Scraping - Clearview AI, HiQ, and Other Controversies
Explore legal and ethical implications of data scraping through case studies like Clearview AI and HiQ, examining privacy concerns and TOS violations.
Logos: Where Privacy, Censorship-Resistance and Permissionlessness Meet
Explore the evolution of decentralized, censorship-resistant infrastructure for preserving digital privacy and free speech, focusing on open-source projects like Waku, Codex, and Nomos.
Unveiling the Mysteries of Digitally Storing the Human Mind
Explore the intricacies of digitally storing human consciousness, delving into mind storage technologies, ethical considerations, and the space required to capture a human mind's essence.
Private Frequency Estimation via Projective Geometry
Explore private frequency estimation using projective geometry with insights from Jelani Nelson's conference talk at CIRM.
On Robustness and Local Differential Privacy
Explore robustness and local differential privacy in mathematical statistics with Thomas Berrett's insightful conference talk at CIRM.
Privacy: Definitions, Procedures, and Open Problems
Explore privacy definitions, procedures, and open problems in mathematical statistics with John Duchi's comprehensive conference talk.
Exploring Data Security in Social Media - Episode 131
Explore data security in social media with insights from former TikTok CISO Roland Cloutier. Gain perspectives on user-generated content, privacy, cybersecurity, and evolving industry challenges.
Clean Forensics: Analyzing Network Traffic of Vacuum Bots - Lecture
Explore network forensics of vacuum bots, uncovering security and privacy concerns. Learn step-by-step analysis of bot communication, authentication protocols, and potential vulnerabilities in smart home devices.
Building a DeGoogled, Privacy-Friendly, and Open Source Mobile Ecosystem - The Story Behind /e/OS
Discover the journey behind /e/OS, a privacy-focused, open-source mobile ecosystem designed to be free from Google's influence.
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models
Explore privacy risks of interactive LLMs, examining evaluation frameworks and proposing research directions for improved privacy auditing and mitigation strategies.
A Unified Analysis of Label Inference Attacks
Explore privacy implications of attribution reporting methods through label inference measures. Gain insights into adversary modeling and risk-accuracy tradeoffs in data privacy.
Machine Unlearning and Privacy Implications - Differential Privacy for ML
Explore privacy implications of machine unlearning, including threat models, deletion inference, and experimental results in this Google TechTalk on differential privacy for ML.
Marginal-based Methods for Differentially Private Synthetic Data - Differential Privacy for ML Series
Explore marginal-based methods for generating differentially private synthetic data, covering mechanisms, selection algorithms, and empirical findings.
Broken Economic Models in Tech That Hurt Humans at Scale
Explore how surveillance capitalism and flawed economic models impact human rights and society. Learn about alternative approaches prioritizing social good, privacy, and human welfare over unchecked growth.
Broken Economic Models in Tech That Hurt Humans at Scale
Explore how surveillance capitalism and current economic models in tech threaten human rights and societal well-being. Learn about potential solutions and actions to prioritize human welfare.
Generating Synthetic Tabular Data that is Differentially Private
Explore approaches to applying differential privacy in generating synthetic tabular data, including measuring low-dimensional distributions and learning graphical model representations for enhanced data privacy.
Privately Evaluating Untrusted Black-Box Functions
Explore tools for sharing sensitive data with untrusted analysts, focusing on differentially private algorithms and privacy wrappers for black-box functions on datasets.
Small Space Differentially Private Graph Algorithms in the Continual Release Model
Explore sublinear space differentially private graph algorithms for continual release, covering densest subgraphs, k-core decomposition, maximum matching, and vertex cover.
Finding PII Reports and Making Your Data Safer in Power BI
Discover techniques to identify PII reports and enhance data protection, including automated methods and tools like Microsoft Purview, DLP, and Defender.