RRC_steganography

RRC Steganography Rotation Range-Coding RRC Steganography — an efficient and provably secure linguistic steganographic method that embeds secret messages into natural-language text generated by large language models. Paper : Efficient Provably Secure Linguistic Steganography via Range Coding How ...

HiTMS_steganography

HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Framework Research code for linguistic steganography over LLM chat dialogues , with a single-stream baseline and a batched multi-stream HiTMS protocol that hides several independent secret messages at once and exploits GPU batching fo...

Safeguarding LLMs against Misuse and AI-Driven Malware Using Steganographic Canaries

AI-powered malware increasingly exploits cloud-hosted generative-AI services and large language models LLMs as analysis engines for reconnaissance and code generation. Simultaneously, enterprise uploads expose sensitive documents to third-party AI vendors. Both threats converge at the AI service...

Exploring AI in Steganography and Steganalysis: Trends, Clusters, and Sustainable Development Potential

Steganography and steganalysis are strongly related subjects of information security. Over the past decade, many powerful and efficient artificial intelligence AI - driven techniques have been designed and presented during research into steganography as well as steganalysis. This study presents a...

TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy Leaking Agent

As large language models LLMs become integrated into sensitive workflows, concerns grow over their potential to leak confidential information. We propose TrojanStego, a novel threat model in which an adversary fine-tunes an LLM to embed sensitive context information into natural-looking outputs v...