A Secure Semantic Communication System Based on Knowledge Graph

TL;DR

This paper introduces a secure semantic communication system utilizing knowledge graphs and advanced encryption techniques to protect textual data, achieving high accuracy for legitimate receivers and low BLEU scores for eavesdroppers.

Contribution

It presents a novel security framework combining knowledge graph preprocessing with a unique channel encryption scheme for semantic communication.

Findings

Reduces probability of information compromise

Achieves BLEU score of 0.9 for legitimate receiver

Improves security by up to 20% compared to baselines

Abstract

This study proposes a novel approach to ensure the security of textual data transmission in a semantic communication system. In the proposed system, a sender transmits textual information to a receiver, while a potential eavesdropper attempts to intercept the information. At the sender side, the text is initially preprocessed, where each sentence is annotated with its corresponding topic, and subsequently extracted into a knowledge graph. To achieve the secure transmission of the knowledge graph, we propose a channel encryption scheme that integrates constellation diagonal transformation with multi-parameter weighted fractional Fourier transform (MP-WFRFT). At the receiver side, the textual data is first decrypted, and then recovered via a transformer model. Experimental results demonstrate that the proposed method reduces the probability of information compromise. The legitimate receiver achieves a Bilingual Evaluation Understudy (BLEU) score of 0.9, whereas the BLEU score of the eavesdropper remains below 0.3. Compared to the baselines, the proposed method can improve the security by up to 20%.