Privacy Preserving Semantic Communications in Wireless Edge Networks with Vision Language Models

2026-08-22

AI Summary

本文提出一种基于视觉-语言模型的隐私保护语义通信框架，通过提取和移除敏感信息，并使用物理层密钥加密文本信息，减少无线边缘网络中的隐私泄露。

Abstract

Semantic communication has emerged as a promising paradigm for next-generation wireless systems by transmitting high-level semantic features rather than raw bits. However, collaborative devices and multimodal transmission increase privacy risks because sensitive information may leak through inter-device semantic fusion and cross-modal representations. To address this issue, we propose a privacy-preserving semantic communication framework for wireless edge networks. Leveraging a vision-language model (VLM), the framework extracts textual semantics from images and identifies privacy-sensitive entities using a privacy database maintained only at the edge server. Before image transmission, each device removes the identified private regions while preserving useful semantic content. The server then reconstructs the removed regions from the received masked images using textual embeddings and VLM-based semantic priors. To protect textual information, we design an encrypted semantic-channel transceiver using physical-layer keys generated from reciprocal wireless channels, without pre-shared keys. We also introduce a semantic information bottleneck to suppress redundant information across multiple devices. The framework is evaluated against a strong model-aware adversary that can intercept wireless transmissions and access edge-device model parameters but not server-side data. Simulation results show that the proposed method reduces privacy leakage by more than 50% compared with a semantic communication scheme without privacy protection, while the authorized server achieves a 48% improvement in perceptual reconstruction quality over the adversary. The estimated mutual information between transmitted representations approaches 0 bit, indicating effective suppression of cross-device semantic redundancy.

Problem

• Privacy Preserving
• Semantic Communication
• Wireless Edge Networks
• Vision-Language Models
• Sensitive Information Leakage

Innovation

• Privacy Preserving
• Semantic Communication
• Vision-Language Model (VLM)
• Edge Networks
• Information Bottleneck