The Privacy-Friendly Tech to Replace Your US-Based Email, Browser, and Search

Thanks to drastic policy changes in the US and Big Tech’s embrace of the second Trump administration, many people are moving their digital lives abroad. Here are a few options to get you started...

TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy Leaking Agent

As large language models LLMs become integrated into sensitive workflows, concerns grow over their potential to leak confidential information. We propose TrojanStego, a novel threat model in which an adversary fine-tunes an LLM to embed sensitive context information into natural-looking outputs v...

DP-RTFL: Differentially Private Resilient Temporal Federated Learning for Trustworthy AI in Regulated Industries

Federated Learning FL has emerged as a critical paradigm for enabling privacy-preserving machine learning, particularly in regulated sectors such as finance and healthcare. However, standard FL strategies often encounter significant operational challenges related to fault tolerance, system...

PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects

The average treatment effect ATE is widely used to evaluate the effectiveness of drugs and other medical interventions. In safety-critical applications like medicine, reliable inferences about the ATE typically require valid uncertainty quantification, such as through confidence intervals CIs...

A Hitchhiker'S Guide to Privacy-Preserving Cryptocurrencies: a Survey on Anonymity, Confidentiality, and Auditability

Cryptocurrencies and central bank digital currencies CBDCs are reshaping the monetary landscape, offering transparency and efficiency while raising critical concerns about user privacy and regulatory compliance. This survey provides a comprehensive and technically grounded overview of...

CISO's Guide To Web Privacy Validation And Why It's Important

Are your web privacy controls protecting your users, or just a box-ticking exercise? This CISO's guide provides a practical roadmap for continuous web privacy validation that's aligned with real-world practices. – Download the full guide here. Web Privacy: From Legal Requirement to Business...

A Starter Guide to Protecting Your Data From Hackers and Corporations

Hackers. AI data scrapes. Government surveillance. Thinking about where to start when it comes to protecting your online privacy can be overwhelming. Here’s a simple guide for you—and anyone who claims they have nothing to hide...

ROS-20250526-07

Google Chrome browser vulnerability involves post-release memory usage. Exploitation of the vulnerability could allow an attacker acting remotely to impact privacy, integrity and availability of data through the use of a specially crafted HTML page...

Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models

Fully decentralized training of machine learning models offers significant advantages in scalability, robustness, and fault tolerance. However, achieving differential privacy DP in such settings is challenging due to the absence of a central aggregator and varying trust assumptions among nodes. I...

Novel Loss-Enhanced Universal Adversarial Patches for Sustainable Speaker Privacy

Deep learning voice models are commonly used nowadays, but the safety processing of personal data, such as human identity and speech content, remains suspicious. To prevent malicious user identification, speaker anonymization methods were proposed. Current methods, particularly based on universal...

Engineering Trustworthy Machine-Learning Operations with Zero-Knowledge Proofs

As Artificial Intelligence AI systems, particularly those based on machine learning ML, become integral to high-stakes applications, their probabilistic and opaque nature poses significant challenges to traditional verification and validation methods. These challenges are exacerbated in regulated...

Evaluating Query Efficiency and Accuracy of Transfer Learning-Based Model Extraction Attack in Federated Learning

Federated Learning FL is a collaborative learning framework designed to protect client data, yet it remains highly vulnerable to Intellectual Property IP threats. Model extraction ME attacks pose a significant risk to Machine Learning as a Service MLaaS platforms, enabling attackers to replicate...

Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models

State-of-the-art membership inference attacks MIAs typically require training many reference models, making it difficult to scale these attacks to large pre-trained language models LLMs. As a result, prior research has either relied on weaker attacks that avoid training reference models e.g.,...

A Study of Semi-Fungible Token Based Wi-Fi Access Control

Current Wi-Fi authentication methods face issues such as insufficient security, user privacy leakage, high management costs, and difficulty in billing. To address these challenges, a Wi-Fi access control solution based on blockchain smart contracts is proposed. Firstly, semi-fungible Wi-Fi tokens...

Understanding the Relationship between Personal Data Privacy Literacy and Data Privacy Information Sharing by University Students

With constant threats to the safety of personal data in the United States, privacy literacy has become an increasingly important competency among university students, one that ties intimately to the information sharing behavior of these students. This survey based study examines how university...

CVE-2025-24116

An access issue was addressed with additional sandbox restrictions. This issue is fixed in macOS Sequoia 15.3, macOS Sonoma 14.7.3, macOS Ventura 13.7.3. An app may be able to bypass Privacy preferences...

CVE-2025-24134

An information disclosure issue was addressed with improved privacy controls. This issue is fixed in macOS Sequoia 15.3. An app may be able to access user-sensitive data...

CVE-2025-24174

The issue was addressed with improved checks. This issue is fixed in macOS Sequoia 15.3, macOS Sonoma 14.7.3, macOS Ventura 13.7.3. An app may be able to bypass Privacy preferences...

CVE-2025-24145

A privacy issue was addressed with improved private data redaction for log entries. This issue is fixed in iOS 18.3 and iPadOS 18.3, macOS Sequoia 15.3. An app may be able to view a contact's phone number in system logs...

CVE-2024-25129

The CodeQL CLI repo holds binaries for the CodeQL command line interface CLI. Prior to version 2.16.3, an XML parser used by the CodeQL CLI to read various auxiliary files is vulnerable to an XML External Entity attack. If a vulnerable version of the CLI is used to process either a maliciously...