A Secure and Efficient Distributed Semantic Communication System for Heterogeneous Internet of Things

TL;DR

This paper presents a secure, efficient distributed semantic communication system for IoT that leverages blockchain trust, flexible semantic coding, and privacy-preserving mechanisms to enhance security, reduce data transmission, and adapt to heterogeneous devices.

Contribution

It introduces a novel blockchain-based trust scheme, a compressive semantic coding method, and a noise-aware differential privacy mechanism for secure, efficient IoT semantic communications.

Findings

Reduces data transmission by 35-88% during updates.

Achieves 60% reduction in data during usage phase.

Ensures integrity and privacy of transmitted semantics.

Abstract

Semantic communications are expected to improve the transmission efficiency in Internet of Things (IoT) networks. However, the distributed nature of networks and heterogeneity of devices challenge the secure utilization of semantic communication systems. In this paper, we develop a distributed semantic communication system that achieves the security and efficiency during update and usage phases. A blockchain-based trust scheme for update is designed to continuously train and synchronize the system in dynamic IoT environments. To improve the updating efficiency, we propose a flexible semantic coding method base on compressive semantic knowledge bases. It greatly reduces the amount of data shared among devices for system update, and realizes the flexible adjustment of the size of knowledge bases and the number of transmitted signal symbols in model training and inference stages. In the usage phase, a signature mechanism for lossy semantics is introduced to guarantee the integrity and authenticity of the transmitted semantics in lossy semantic communications. We further design a noise-aware differential privacy mechanism, which introduces optimized noise based on the different channel information available to heterogeneous devices. Experiments on text transmission tasks show that the proposed system achieves the protection of the integrity and privacy for exchanged semantics, and reduces the data to be transmitted in the update phase by about $35\%$ to $88\%$, and in the usage phase by $60\%$ compared with related works.