openstego

OpenStego OpenStego è un'applicazione di steganografia che offre due funzionalità: 1. Nascondere dati: può nascondere qualsiasi dato all'interno di un file immagine. 2. Watermarking: applica una firma invisibile ai file immagine. Può essere usato per rilevare copie non autorizzate. Utilizzo Per...

openstego

OpenStego OpenStego is a steganography application that provides two functionalities: 1. Data Hiding: It can hide any data within an image file. 2. Watermarking: Watermarking image files with an invisible signature. It can be used to detect unauthorized file copying. Usage For GUI: Use menu...

nullorigin

NullOrigin 🛡️ Universelle Middleware für KI-Herkunftsnachweis & Wasserzeichen-Sanitisierung Forschungsartefakt — nur zur Bewertung der Robustheit von Wasserzeichen. 🔬 Nur für Forschungszwecke NullOrigin ist ein Forschungsartefakt. Es wird veröffentlicht, um die akademische und unabhängige...

Watermark_Spoofing

ВЛИЯНИЕ ВСТРАИВАНИЯ ВОДЯНЫХ ЗНАКОВ В АУДИО НА КОНТРМЕРЫ АНТИ-СПУФИНГА Этот репозиторий содержит официальную реализацию нашей статьи: THE IMPACT OF AUDIO WATERMARKING ON AUDIO ANTI-SPOOFING COUNTERMEASURES . Интерактивное демо и визуализации доступны здесь. Что внутри 1. Набор данных...

CC_Watermark

用于无失真文本水印的最优耦合 用于无失真文本水印的最优耦合 的官方代码 摘要 大型语言模型（LLM）现在能够生成与人类内容无法区分的文本。 这推动了水印技术的发展，水印通过在 LLM 生成的文本中印记"信号"，同时对 LLM 输出的扰动最小。 本文对一次性（one-shot）场景下的文本水印进行了分析。 通过带辅助信息的假设检验视角，我们系统地阐述并分析了水印检测能力与生成文本质量失真之间的基本权衡。 我们认为水印设计的一个关键组成部分是在与水印检测器共享的辅助信息与 LLM 词汇表的随机划分之间生成一种耦合。 我们的分析确定了在满足最小熵约束的最坏情况 LLM...

Stego-Lab

Stego-Lab Esteganografia. EXIF. Marcas d'água. Decodificar. Lote. Fluxos de trabalho profissionais de privacidade de imagem para iPhone, iPad e macOS. Site · GitLab · Página do Projeto · Política de Privacidade · Kit de Imprensa · Suporte · Licença Por que Stego-Lab O Stego-Lab reúne fluxos de...

covertchannels-steganography

Molte persone mi chiedono come iniziare nel campo della steganografia/dei canali covert o come migliorare le proprie capacità. Ho scritto questa raccolta per aiutarle con alcune buone referenze, strumenti e libri che ho usato e letto presto ne aggiungerò altri. Libri e articoli Tecniche di...

From Noise to Meaning: Meaningful Secret Sharing with Tamper Detection for Facial Recognition

Popularity of AI-based face recognition system directly demands protection of sensitive biometric data used for training. Visual secret sharing is an interesting idea, as it splits facial images into secret shares that look random and spread across many institutions. However, these shares look li...

Cryptanalysis of Pseudorandom Error-Correcting Codes

Pseudorandom error-correcting codes PRC is a novel cryptographic primitive proposed at CRYPTO 2024. Due to the dual capability of pseudorandomness and error correction, PRC has been recognized as a promising foundational component for watermarking AI-generated content. However, the security of PR...

Security and Detectability Analysis of Unicode Text Watermarking Methods against Large Language Models

Securing digital text is becoming increasingly relevant due to the widespread use of large language models. Individuals' fear of losing control over data when it is being used to train such machine learning models or when distinguishing model-generated output from text written by humans. Digital...

DITTO: A Spoofing Attack Framework on Watermarked LLMs Via Knowledge Distillation

The promise of LLM watermarking rests on a core assumption that a specific watermark proves authorship by a specific model. We demonstrate that this assumption is dangerously flawed. We introduce the threat of watermark spoofing, a sophisticated attack that allows a malicious model to generate te...

The Impact of Audio Watermarking on Audio Anti-Spoofing Countermeasures

This paper presents the first study on the impact of audio watermarking on spoofing countermeasures. While anti-spoofing systems are essential for securing speech-based applications, the influence of widely used audio watermarking, originally designed for copyright protection, remains largely...

Cryptographic Backdoor for Neural Networks: Boon and Bane

In this paper we show that cryptographic backdoors in a neural network NN can be highly effective in two directions, namely mounting the attacks as well as in presenting the defenses as well. On the attack side, a carefully planted cryptographic backdoor enables powerful and invisible attack on t...

Risk Assessment and Security Analysis of Large Language Models

As large language models LLMs expose systemic security challenges in high risk applications, including privacy leaks, bias amplification, and malicious abuse, there is an urgent need for a dynamic risk assessment and collaborative defence framework that covers their entire life cycle. This paper...

Hot-Swap MarkBoard: an Efficient Black-Box Watermarking Approach for Large-Scale Model Distribution

Recently, Deep Learning DL models have been increasingly deployed on end-user devices as On-Device AI, offering improved efficiency and privacy. However, this deployment trend poses more serious Intellectual Property IP risks, as models are distributed on numerous local devices, making them...

Removing Box-Free Watermarks for Image-To-Image Models Via Query-Based Reverse Engineering

The intellectual property of deep generative networks GNets can be protected using a cascaded hiding network HNet which embeds watermarks or marks into GNet outputs, known as box-free watermarking. Although both GNet and HNet are encapsulated in a black box called operation network, or ONet, with...

WaveVerify: a Novel Audio Watermarking Framework for Media Authentication and Combatting Deepfakes

The rapid advancement of voice generation technologies has enabled the synthesis of speech that is perceptually indistinguishable from genuine human voices. While these innovations facilitate beneficial applications such as personalized text-to-speech systems and voice preservation, they have als...

Mitigating Watermark Stealing Attacks in Generative Models Via Multi-Key Watermarking

Watermarking offers a promising solution for GenAI providers to establish the provenance of their generated content. A watermark is a hidden signal embedded in the generated content, whose presence can later be verified using a secret watermarking key. A threat to GenAI providers are \emphwaterma...

Semi-Fragile Watermarking of Remote Sensing Images Using DWT, Vector Quantization and Automatic Tiling

A semi-fragile watermarking scheme for multiple band images is presented in this article. We propose to embed a mark into remote sensing images applying a tree-structured vector quantization approach to the pixel signatures instead of processing each band separately. The signature of the...

README: Robust Error-Aware Digital Signature Framework Via Deep Watermarking Model

Deep learning-based watermarking has emerged as a promising solution for robust image authentication and protection. However, existing models are limited by low embedding capacity and vulnerability to bit-level errors, making them unsuitable for cryptographic applications such as digital...