EUVD-2024-29864

Malicious code in bioql PyPI...

EUVD-2025-7001

Malicious code in bioql PyPI...

EUVD-2025-7011

Malicious code in bioql PyPI...

EUVD-2024-29860

Malicious code in bioql PyPI...

EUVD-2025-16160

Malicious code in bioql PyPI...

EUVD-2024-29865

Malicious code in bioql PyPI...

EUVD-2024-29344

Malicious code in bioql PyPI...

EUVD-2024-29862

Malicious code in bioql PyPI...

EUVD-2025-7060

Malicious code in bioql PyPI...

EUVD-2025-7024

Malicious code in bioql PyPI...

Topology Generation of UAV Covert Communication Networks: a Graph Diffusion Approach with Incentive Mechanism

With the growing demand for Uncrewed Aerial Vehicle UAV networks in sensitive applications, such as urban monitoring, emergency response, and secure sensing, ensuring reliable connectivity and covert communication has become increasingly vital. However, dynamic mobility and exposure risks pose...

From Split to Share: Private Inference with Distributed Feature Sharing

Cloud-based Machine Learning as a Service MLaaS raises serious privacy concerns when handling sensitive client data. Existing Private Inference PI methods face a fundamental trade-off between privacy and efficiency: cryptographic approaches offer strong protection but incur high computational...

BadBlocks: Low-Cost and Stealthy Backdoor Attacks Tailored for Text-To-Image Diffusion Models

In recent years,Diffusion models have achieved remarkable progress in the field of image generation.However,recent studies have shown that diffusion models are susceptible to backdoor attacks,in which attackers can manipulate the output by injecting covert triggers such as specific visual pattern...

EdgeAgentX-DT: Integrating Digital Twins and Generative AI for Resilient Edge Intelligence in Tactical Networks

We introduce EdgeAgentX-DT, an advanced extension of the EdgeAgentX framework that integrates digital twin simulations and generative AI-driven scenario training to significantly enhance edge intelligence in military networks. EdgeAgentX-DT utilizes network digital twins, virtual replicas...

Generating Adversarial Point Clouds Using Diffusion Model

Adversarial attack methods for 3D point cloud classification reveal the vulnerabilities of point cloud recognition models. This vulnerability could lead to safety risks in critical applications that use deep learning models, such as autonomous vehicles. To uncover the deficiencies of these models...

An Improved ChaCha Algorithm Based on Quantum Random Number

Due to the merits of high efficiency and strong security against timing and side-channel attacks, ChaCha has been widely applied in real-time communication and data streaming scenarios. However, with the rapid development of AI-assisted cryptanalysis and quantum computing technologies, there are...

WaFusion: a Wavelet-Enhanced Diffusion Framework for Face Morph Generation

Biometric face morphing poses a critical challenge to identity verification systems, undermining their security and robustness. To address this issue, we propose WaFusion, a novel framework combining wavelet decomposition and diffusion models to generate high-quality, realistic morphed face image...

SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts

Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized modifications. To address this, we propose SecureT2I, a secure framework designed to prevent unauthorized editing in...

Machine Learning with Privacy for Protected Attributes

Differential privacy DP has become the standard for private data analysis. Certain machine learning applications only require privacy protection for specific protected attributes. Using naive variants of differential privacy in such use cases can result in unnecessary degradation of utility. In...

Diffusion-Based Task-Oriented Semantic Communications with Model Inversion Attack

Semantic communication has emerged as a promising neural network-based system design for 6G networks. Task-oriented semantic communication is a novel paradigm whose core goal is to efficiently complete specific tasks by transmitting semantic information, optimizing communication efficiency and ta...