Secure Intellicise Wireless Network: Agentic AI for Coverless Semantic Steganography Communication

TL;DR

This paper introduces AgentSemSteCom, an agentic AI-based semantic steganographic communication scheme that enhances security and capacity in wireless networks by eliminating the need for cover images and private keys.

Contribution

It proposes a novel AI-driven semantic steganography method that improves security and capacity without relying on cover images or private semantic keys.

Findings

Achieves better transmission quality than baseline schemes.

Provides higher security levels in semantic steganography.

Boosts steganographic capacity through innovative techniques.

Abstract

Semantic Communication (SemCom), leveraging its significant advantages in transmission efficiency and reliability, has emerged as a core technology for constructing future intellicise (intelligent and concise) wireless networks. However, intelligent attacks represented by semantic eavesdropping pose severe challenges to the security of SemCom. To address this challenge, Semantic Steganographic Communication (SemSteCom) achieves ``invisible'' encryption by implicitly embedding private semantic information into cover modality carriers. The state-of-the-art study has further introduced generative diffusion models to directly generate stega images without relying on original cover images, effectively enhancing steganographic capacity. Nevertheless, the recovery process of private images is highly dependent on the guidance of private semantic keys, which may be inferred by intelligent eavesdroppers, thereby introducing new security threats. To address this issue, we propose an Agentic AI-driven SemSteCom (AgentSemSteCom) scheme, which includes semantic extraction, digital token controlled reference image generation, coverless steganography, semantic codec, and optional task-oriented enhancement modules. The proposed AgentSemSteCom scheme obviates the need for both cover images and private semantic keys, thereby boosting steganographic capacity while reinforcing transmission security. The simulation results on open-source datasets verify that, AgentSemSteCom achieves better transmission quality and higher security levels than the baseline scheme.