Rethinking Security of Diffusion-Based Generative Steganography

Generative image steganography is a technique that conceals secret messages within generated images, without relying on pre-existing cover images. Recently, a number of diffusion model-based generative image steganography DM-GIS methods have been introduced, which effectively combat traditional...

Diffusion-Driven Deceptive Patches: Adversarial Manipulation and Forensic Detection in Facial Identity Verification

This work presents an end-to-end pipeline for generating, refining, and evaluating adversarial patches to compromise facial biometric systems, with applications in forensic analysis and security testing. We utilize FGSM to generate adversarial noise targeting an identity classifier and employ a...

RoBCtrl: Attacking GNN-Based Social Bot Detectors Via Reinforced Manipulation of Bots Control Interaction

Social networks have become a crucial source of real-time information for individuals. The influence of social bots within these platforms has garnered considerable attention from researchers, leading to the development of numerous detection technologies. However, the vulnerability and robustness...

Targeted Pooled Latent-Space Steganalysis Applied to Generative Steganography, with a Fix

Steganographic schemes dedicated to generated images modify the seed vector in the latent space to embed a message, whereas most steganalysis methods attempt to detect the embedding in the image space. This paper proposes to perform steganalysis in the latent space by modeling the statistical...

EMPalm: Exfiltrating Palm Biometric Data Via Electromagnetic Side-Channels

Palm recognition has emerged as a dominant biometric authentication technology in critical infrastructure. These systems operate in either single-modal form, using palmprint or palmvein individually, or dual-modal form, fusing the two modalities. Despite this diversity, they share similar hardwar...

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...

Restoring Gaussian Blurred Face Images for Deanonymization Attacks

Gaussian blur is widely used to blur human faces in sensitive photos before the photos are posted on the Internet. However, it is unclear to what extent the blurred faces can be restored and used to re-identify the person, especially under a high-blurring setting. In this paper, we explore this...

Removing Watermarks with Partial Regeneration Using Semantic Information

As AI-generated imagery becomes ubiquitous, invisible watermarks have emerged as a primary line of defense for copyright and provenance. The newest watermarking schemes embed semantic signals - content-aware patterns that are designed to survive common image manipulations - yet their true...

GTSD: Generative Text Steganography Based on Diffusion Model

With the rapid development of deep learning, existing generative text steganography methods based on autoregressive models have achieved success. However, these autoregressive steganography approaches have certain limitations. Firstly, existing methods require encoding candidate words according t...

ComfyUI 跨站请求伪造漏洞

ComfyUI is one of the most powerful and modular diffusion model GUIs and backends from comfyanonymous individual developers. A cross-site request forgery vulnerability exists in ComfyUI v0.2.2 and prior versions, which stems from insufficient CSRF protection and could lead to unauthorized API...

Deserialization of Untrusted Data

Overview Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the torch.load function within the Checkpoint.loadcheckpoint method without restrictions. Details Serialization is a process of converting an object into a sequence of bytes which can be persisted t...