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

Bizhu Wang, Zhiqiang Bian, Yue Chen, Xiaodong Xu, Chen Sun, Wenqi Zhang, Ping Zhang

TL;DR

This paper tackles secure semantic communications for intelligent connected vehicles by integrating cryptography into SemCom to prevent eavesdropping without heavy key management. It introduces Efficient Semantic-aware Encryption (ESAE), which derives identical session keys at both ends from past semantic content (semantic reciprocity) and employs a semantic-aware key pre-processing (SA-KP) using YOLOv10 to extract consistent semantics for key generation. A formal Mean Consistency Rate of Semantic Key Generation (MCR-SKG) metric is proposed to quantify key alignment, and security analysis shows that semantic key space is larger than traditional bit-level spaces under practical parameters. Simulations on COCO and NTSCC demonstrate ESAE’s ability to reduce key transmission overhead while maintaining semantic fidelity and security, with performance depending on hyperparameters like window size $\mathcal{T}$, top-$K$ objects, and grid divisions $Q$.

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.

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

TL;DR

This paper tackles secure semantic communications for intelligent connected vehicles by integrating cryptography into SemCom to prevent eavesdropping without heavy key management. It introduces Efficient Semantic-aware Encryption (ESAE), which derives identical session keys at both ends from past semantic content (semantic reciprocity) and employs a semantic-aware key pre-processing (SA-KP) using YOLOv10 to extract consistent semantics for key generation. A formal Mean Consistency Rate of Semantic Key Generation (MCR-SKG) metric is proposed to quantify key alignment, and security analysis shows that semantic key space is larger than traditional bit-level spaces under practical parameters. Simulations on COCO and NTSCC demonstrate ESAE’s ability to reduce key transmission overhead while maintaining semantic fidelity and security, with performance depending on hyperparameters like window size , top- objects, and grid divisions .

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.

Paper Structure

This paper contains 16 sections, 3 equations, 7 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Proposed ESAE Mechanism
  4. Initialization Phase
  5. Initial Secure Semantic Transmission
  6. Semantic Session Key Generation and Update
  7. Subsequent Secure Semantic Transmission
  8. Proposed SA-KP Mechanism
  9. Performance Evaluation
  10. Simulation Settings
  11. Data set
  12. ESAE implementation
  13. Evaluation Metrics
  14. Security Analysis
  15. Simulation Results and Analysis
  16. ...and 1 more sections

Figures (7)

  • Figure 1: Diagram of SemCom-enabled ICVs
  • Figure 2: Flowchart of encryption-enabled SemCom ICVs
  • Figure 3: Procedure for semantic-aware session key generation and update in ESAE (channel encoding/decoding omitted for simplicity)
  • Figure 4: Diagram of SA-KP for semantic key generation
  • Figure 5: The visualization of SA-KP outputs when $\mathcal{T}=1$ and SNR=25 dB
  • ...and 2 more figures