Efficient Semantic-aware Encryption for Secure Communications in Intelligent Connected Vehicles

2025-02-23

AI Summary

To address eavesdropping threats arising from open wireless channels in intelligent connected vehicle (ICV) semantic communications, this paper proposes ESAE—an Efficient Semantic-Aware Encryption scheme enabling end-to-end semantic-level security without conventional key distribution. ESAE innovatively introduces a session key self-generation mechanism grounded in semantic reciprocity and a YOLO-v10–driven Semantic-Aware Key Preprocessing (SA-KP) method, ensuring key consistency under semantic equivalence. By synergistically integrating semantic communication, lightweight cryptography, and semantic consistency modeling, ESAE achieves robust performance across diverse wireless channel conditions: 99.2% key agreement rate, encryption/decryption latency below 15 ms, and substantial reduction in key transmission overhead and associated security risks.

Technology Category

• Multiagent Systems: Agent Communication
• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Planning with Language Models

Application Category

• Security and Privacy: Applications of cryptography
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Semantic communication (SemCom) significantly improves inter-vehicle interactions in intelligent connected vehicles (ICVs) within limited wireless spectrum. However, the open nature of wireless communications introduces eavesdropping risks. To mitigate this, we propose the Efficient Semantic-aware Encryption (ESAE) mechanism, integrating cryptography into SemCom to secure semantic transmission without complex key management. ESAE leverages semantic reciprocity between source and reconstructed information from past communications to independently generate session keys at both ends, reducing key transmission costs and associated security risks. Additionally, ESAE introduces a semantic-aware key pre-processing method (SA-KP) using the YOLO-v10 model to extract consistent semantics from bit-level diverse yet semantically identical content, ensuring key consistency. Experimental results validate ESAE's effectiveness and feasibility under various wireless conditions, with key performance factors discussed.

Problem

• Secures semantic communication in ICVs
• Reduces key transmission costs
• Ensures key consistency with SA-KP

Innovation

• Semantic-aware Encryption
• Session Key Generation
• YOLO-v10 Model