Revisiting Adversarial Perception Attacks and Defense Methods on Autonomous Driving Systems

Autonomous driving systems ADS increasingly rely on deep learning-based perception models, which remain vulnerable to adversarial attacks. In this paper, we revisit adversarial attacks and defense methods, focusing on road sign recognition and lead object detection and prediction e.g., relative...

PT-2025-22503 · Unknown · Fc-Stable-Diffusion-Plus

Name of the Vulnerable Software and Affected Versions: fc-stable-diffusion-plus version 1.0.18 Description: The issue is related to insecure permissions, which can allow attackers to escalate privileges and compromise the customer cloud account. Recommendations: For fc-stable-diffusion-plus versi...

CVE-2025-45468

Insecure permissions in fc-stable-diffusion-plus v1.0.18 allows attackers to escalate privileges and compromise the customer cloud account...

fc-stable-diffusion 安全漏洞

fc-stable-diffusion is an open source tool from Serverless Devs Registry for deploying stable-diffusion to AliCloud Functional Computing. A security vulnerability exists in fc-stable-diffusion v1.0.18, which stems from improper privileges and could lead to elevated privileges and customer cloud...

CVE-2025-45468

CVE-2025-45468 affects fc-stable-diffusion-plus v1.0.18, caused by insecure permissions that enable privilege escalation and potential compromise of the customer cloud account. CVSS 3.1 base score 8.8 (HIGH) with network attack vector, low attack complexity, and privileges required: LOW. Exploita...

CVE-2025-45468

Insecure permissions in fc-stable-diffusion-plus v1.0.18 allows attackers to escalate privileges and compromise the customer cloud account...

Gaussian Shading++: Rethinking the Realistic Deployment Challenge of Performance-Lossless Image Watermark for Diffusion Models

Ethical concerns surrounding copyright protection and inappropriate content generation pose challenges for the practical implementation of diffusion models. One effective solution involves watermarking the generated images. Existing methods primarily focus on ensuring that watermark embedding doe...

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...

Real-Time Bit-Level Encryption of Full High-Definition Video without Diffusion

Despite the widespread adoption of Shannon's confusion-diffusion architecture in image encryption, the implementation of diffusion to sequentially establish inter-pixel dependencies for attaining plaintext sensitivity constrains algorithmic parallelism, while the execution of multiple rounds of...

Towards Dataset Copyright Evasion Attack against Personalized Text-To-Image Diffusion Models

Text-to-image T2I diffusion models have rapidly advanced, enabling high-quality image generation conditioned on textual prompts. However, the growing trend of fine-tuning pre-trained models for personalization raises serious concerns about unauthorized dataset usage. To combat this, dataset...

VIDSTAMP: a Temporally-Aware Watermark for Ownership and Integrity in Video Diffusion Models

The rapid rise of video diffusion models has enabled the generation of highly realistic and temporally coherent videos, raising critical concerns about content authenticity, provenance, and misuse. Existing watermarking approaches, whether passive, post-hoc, or adapted from image-based techniques...

Erased but Not Forgotten: How Backdoors Compromise Concept Erasure

The expansion of large-scale text-to-image diffusion models has raised growing concerns about their potential to generate undesirable or harmful content, ranging from fabricated depictions of public figures to sexually explicit images. To mitigate these risks, prior work has devised machine...

DICOM Compatible, 3D Multimodality Image Encryption Using Hyperchaotic Signal

Medical image encryption plays an important role in protecting sensitive health information from cyberattacks and unauthorized access. In this paper, we introduce a secure and robust encryption scheme that is multi-modality compatible and works with MRI, CT, X-Ray and Ultrasound images for...

GenPTW: In-Generation Image Watermarking for Provenance Tracing and Tamper Localization

The rapid development of generative image models has brought tremendous opportunities to AI-generated content AIGC creation, while also introducing critical challenges in ensuring content authenticity and copyright ownership. Existing image watermarking methods, though partially effective, often...

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...

Blockchain Meets Adaptive Honeypots: a Trust-Aware Approach to Next-Gen IoT Security

Edge computing-based Next-Generation Wireless Networks NGWN-IoT offer enhanced bandwidth capacity for large-scale service provisioning but remain vulnerable to evolving cyber threats. Existing intrusion detection and prevention methods provide limited security as adversaries continually adapt the...

Adversarial Observations in Weather Forecasting

AI-based systems, such as Google's GenCast, have recently redefined the state of the art in weather forecasting, offering more accurate and timely predictions of both everyday weather and extreme events. While these systems are on the verge of replacing traditional meteorological methods, they al...

Backdoor Defense in Diffusion Models Via Spatial Attention Unlearning

Text-to-image diffusion models are increasingly vulnerable to backdoor attacks, where malicious modifications to the training data cause the model to generate unintended outputs when specific triggers are present. While classification models have seen extensive development of defense mechanisms,...

What Lurks Within? Concept Auditing for Shared Diffusion Models at Scale

Diffusion models DMs have revolutionized text-to-image generation, enabling the creation of highly realistic and customized images from text prompts. With the rise of parameter-efficient fine-tuning PEFT techniques like LoRA, users can now customize powerful pre-trained models using minimal...

REDEditing: Relationship-Driven Precise Backdoor Poisoning on Text-To-Image Diffusion Models

The rapid advancement of generative AI highlights the importance of text-to-image T2I security, particularly with the threat of backdoor poisoning. Timely disclosure and mitigation of security vulnerabilities in T2I models are crucial for ensuring the safe deployment of generative models. We...