14263 matches found
DynaNoise: Dynamic Probabilistic Noise Injection for Defending against Membership Inference Attacks
Membership Inference Attacks MIAs pose a significant risk to the privacy of training datasets by exploiting subtle differences in model outputs to determine whether a particular data sample was used during training. These attacks can compromise sensitive information, especially in domains such as...
WordPress plugin GDPR CCPA Compliance Support 安全漏洞
WordPress and WordPress plugin are both products of the WordPress Foundation. WordPress is a blogging platform developed in the PHP language. The platform supports personal blog sites on PHP and MySQL servers.WordPress plugin is an application plugin. A security vulnerability exists in WordPress...
Outsourced Privacy-Preserving Feature Selection Based on Fully Homomorphic Encryption
Feature selection is a technique that extracts a meaningful subset from a set of features in training data. When the training data is large-scale, appropriate feature selection enables the removal of redundant features, which can improve generalization performance, accelerate the training process...
Cross-Cloud Data Privacy Protection: Optimizing Collaborative Mechanisms of AI Systems by Integrating Federated Learning and LLMs
In the age of cloud computing, data privacy protection has become a major challenge, especially when sharing sensitive data across cloud environments. However, how to optimize collaboration across cloud environments remains an unresolved problem. In this paper, we combine federated learning with...
Private Statistical Estimation Via Truncation
We introduce a novel framework for differentially private DP statistical estimation via data truncation, addressing a key challenge in DP estimation when the data support is unbounded. Traditional approaches rely on problem-specific sensitivity analysis, limiting their applicability. By leveragin...
CVE-2025-48219
O2 UK before 2025-05-19 allows subscribers to determine the Cell ID of other subscribers by initiating an IMS IP Multimedia Subsystem call and then reading the utran-cell-id-3gpp field of a Cellular-Network-Info SIP header, aka an ECI E-UTRAN Cell Identity leak. The Cell ID might be usable to...
PoLO: Proof-Of-Learning and Proof-Of-Ownership at Once with Chained Watermarking
Machine learning models are increasingly shared and outsourced, raising requirements of verifying training effort Proof-of-Learning, PoL to ensure claimed performance and establishing ownership Proof-of-Ownership, PoO for transactions. When models are trained by untrusted parties, PoL and PoO mus...
ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation
The development of artificial intelligence demands that models incrementally update knowledge by Continual Learning CL to adapt to open-world environments. To meet privacy and security requirements, Continual Unlearning CU emerges as an important problem, aiming to sequentially forget particular...
Automated Profile Inference with Language Model Agents
Impressive progress has been made in automated problem-solving by the collaboration of large language models LLMs based agents. However, these automated capabilities also open avenues for malicious applications. In this paper, we study a new threat that LLMs pose to online pseudonymity, called...
Exploit for Out-of-bounds Write in Apple Macos
CVE-2025-31200 & CVE-2025-31201 | iMessage Zero-Click RCE Chai...
Privacy-Preserving AI for Encrypted Medical Imaging: a Framework for Secure Diagnosis and Learning
The rapid integration of Artificial Intelligence AI into medical diagnostics has raised pressing concerns about patient privacy, especially when sensitive imaging data must be transferred, stored, or processed. In this paper, we propose a novel framework for privacy-preserving diagnostic inferenc...
Proof-Of-Social-Capital: Privacy-Preserving Consensus Protocol Replacing Stake for Social Capital
Consensus protocols used today in blockchains often rely on computational power or financial stakes - scarce resources. We propose a novel protocol using social capital - trust and influence from social interactions - as a non-transferable staking mechanism to ensure fairness and decentralization...
On Membership Inference Attacks in Knowledge Distillation
Nowadays, Large Language Models LLMs are trained on huge datasets, some including sensitive information. This poses a serious privacy concern because privacy attacks such as Membership Inference Attacks MIAs may detect this sensitive information. While knowledge distillation compresses LLMs into...
Meta sent cease and desist letter over AI training
EU privacy advocacy group NOYB has clapped back at Meta over its plans to start training its AI model on European users' data. In a cease and desist letter to the social networking giant's Irish operation signed by founder Max Schrems, the non-profit demanded that it justify its actions or risk...
CVE-2025-47930
Zulip is an open-source team chat application. Starting in version 10.0 and prior to version 10.3, the "Who can create public channels" access control mechanism can be circumvented by creating a private or web-public channel, and then changing the channel privacy to public. A similar technique...
PIG: Privacy Jailbreak Attack on LLMs Via Gradient-Based Iterative In-Context Optimization
Large Language Models LLMs excel in various domains but pose inherent privacy risks. Existing methods to evaluate privacy leakage in LLMs often use memorized prefixes or simple instructions to extract data, both of which well-alignment models can easily block. Meanwhile, Jailbreak attacks bypass...
Anti-Sensing: Defense against Unauthorized Radar-Based Human Vital Sign Sensing with Physically Realizable Wearable Oscillators
Recent advancements in Ultra-Wideband UWB radar technology have enabled contactless, non-line-of-sight vital sign monitoring, making it a valuable tool for healthcare. However, UWB radar's ability to capture sensitive physiological data, even through walls, raises significant privacy concerns,...
Privacy and Confidentiality Requirements Engineering for Process Data
The application and development of process mining techniques face significant challenges due to the lack of publicly available real-life event logs. One reason for companies to abstain from sharing their data are privacy and confidentiality concerns. Privacy concerns refer to personal data as...
Optimal Allocation of Privacy Budget on Hierarchical Data Release
Releasing useful information from datasets with hierarchical structures while preserving individual privacy presents a significant challenge. Standard privacy-preserving mechanisms, and in particular Differential Privacy, often require careful allocation of a finite privacy budget across differen...
