Blue Shield Leaked Millions of Patient Info to Google for Years

Blue Shield of California exposed the health data of 4.7 million members to Google for years due to…...

WhatsApp Adds Advanced Chat Privacy to Blocks Chat Exports and Auto-Downloads

WhatsApp has introduced an extra layer of privacy called Advanced Chat Privacy that allows users to block participants from sharing the contents of a conversation in traditional chats and groups. "This new setting available in both chats and groups helps prevent others from taking content outside...

Optimizing the Privacy-Utility Balance Using Synthetic Data and Configurable Perturbation Pipelines

This paper explores the strategic use of modern synthetic data generation and advanced data perturbation techniques to enhance security, maintain analytical utility, and improve operational efficiency when managing large datasets, with a particular focus on the Banking, Financial Services, and...

Silenzio: Secure Non-Interactive Outsourced MLP Training

Outsourcing the ML training to cloud providers presents a compelling opportunity for resource constrained clients, while it simultaneously bears inherent privacy risks, especially for highly sensitive training data. We introduce Silenzio, the first fully non-interactive outsourcing scheme for the...

CVE-2023-45720: Exposure of Private Personal Information to an Unauthorized Actor

Insufficient default configuration in HCL Leap allows anonymous access to directory information...

Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction

With the rapid digitalization of healthcare systems, there has been a substantial increase in the generation and sharing of private health data. Safeguarding patient information is essential for maintaining consumer trust and ensuring compliance with legal data protection regulations. Machine...

From Randomized Response to Randomized Index: Answering Subset Counting Queries with Local Differential Privacy

Local Differential Privacy LDP is the predominant privacy model for safeguarding individual data privacy. Existing perturbation mechanisms typically require perturbing the original values to ensure acceptable privacy, which inevitably results in value distortion and utility deterioration. In this...

Shopify faces privacy lawsuit for collecting customer data

Shopify faces a data privacy class action lawsuit in the US that could change the way globally active companies can be held accountable. The proposed class action is a revival of a case that had been dismissed by a lower court judge and a three-judge 9th Circuit Court of Appeals panel. But now it...

Lattica Emerges from Stealth to Solve AI’s Biggest Privacy Challenge with FHE

Lattica’s cloud-based solution uses Fully Homomorphic Encryption to query encrypted data on AI models without decrypting it, preserving privacy and bolstering security...

Google Drops Cookie Prompt in Chrome, Adds IP Protection to Incognito

Google on Tuesday revealed that it will no longer offer a standalone prompt for third-party cookies in its Chrome browser as part of its Privacy Sandbox initiative. "We've made the decision to maintain our current approach to offering users third-party cookie choice in Chrome, and will not be...

AiXamine: Simplified LLM Safety and Security

Evaluating Large Language Models LLMs for safety and security remains a complex task, often requiring users to navigate a fragmented landscape of ad hoc benchmarks, datasets, metrics, and reporting formats. To address this challenge, we present aiXamine, a comprehensive black-box evaluation...

Developing a Blockchain-Based Secure Digital Contents Distribution System

As digital content distribution expands rapidly through online platforms, securing digital media and protecting intellectual property has become increasingly complex. Traditional centralized systems, while widely adopted, suffer from vulnerabilities such as single points of failure and limited...

Private Federated Learning Using Preference-Optimized Synthetic Data

In practical settings, differentially private Federated learning DP-FL is the dominant method for training models from private, on-device client data. Recent work has suggested that DP-FL may be enhanced or outperformed by methods that use DP synthetic data Wu et al., 2024; Hou et al., 2024. The...

CVE-2025-3645

A flaw was found in Moodle. Insufficient capability checks in a messaging web service allowed users to view other users' names and online statuses...

Quantifying Source Speaker Leakage in One-To-One Voice Conversion

Using a multi-accented corpus of parallel utterances for use with commercial speech devices, we present a case study to show that it is possible to quantify a degree of confidence about a source speaker's identity in the case of one-to-one voice conversion. Following voice conversion using a...

On the Price of Differential Privacy for Hierarchical Clustering

Hierarchical clustering is a fundamental unsupervised machine learning task with the aim of organizing data into a hierarchy of clusters. Many applications of hierarchical clustering involve sensitive user information, therefore motivating recent studies on differentially private hierarchical...

Charting the Uncharted: the Landscape of Monero Peer-To-Peer Network

The Monero blockchain enables anonymous transactions through advanced cryptography in its peer-to-peer network, which underpins decentralization, security, and trustless interactions. However, privacy measures obscure peer connections, complicating network analysis. This study proposes a method t...

Intelligent Detection of Non-Essential IoT Traffic on the Home Gateway

The rapid expansion of Internet of Things IoT devices, particularly in smart home environments, has introduced considerable security and privacy concerns due to their persistent connectivity and interaction with cloud services. Despite advancements in IoT security, effective privacy measures rema...

How Private Is Your Attention? Bridging Privacy with In-Context Learning

In-context learning ICL-the ability of transformer-based models to perform new tasks from examples provided at inference time-has emerged as a hallmark of modern language models. While recent works have investigated the mechanisms underlying ICL, its feasibility under formal privacy constraints...

Did DOGE “breach” Americans’ data? (Lock and Code S06E08)

This week on the Lock and Code podcast … If you don't know about the newly created US Department of Government Efficiency DOGE, there's a strong chance they already know about you. Created on January 20 by US President Donald Trump through Executive Order, DOGE's broad mandate is “modernizing...