信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2026, Vol. 52 ›› Issue (1): 18-23.doi: 10.12267/j.issn.2096-5931.2026.01.003

专题:新型工业网络技术与产业创新发展 上一篇    下一篇

面向通感一体化的安全需求与关键技术分析*

Analysis of safety requirements and key technologies for the integration of vision and auditory sensation

熊子懿1,2, 石慧1, 王明月1,2   

  1. 1.重庆移通学院,重庆 401420
    2.公共大数据安全技术重庆市重点实验室,重庆 401420
  • 收稿日期:2025-12-16 出版日期:2026-01-25 发布日期:2026-01-28
  • 通讯作者: 熊子懿
  • 作者简介:
    石慧, 重庆移通学院本科生在读,主要研究方向为通信工程与技术
    王明月, 重庆移通学院副教授,博士,主要研究方向为电子信息、通信协议等
  • 基金资助:
    重庆市教委科学技术研究计划青年项目(KJQN202202401);重庆市教委科学技术研究计划青年项目(KJQN202302402);重庆市教委科学技术研究计划重点项目(KJZD-K202302401)

XIONG Ziyi1,2, SHI Hui1, WANG Mingyue1,2   

  1. 1. Chongqing College of Mobile Communication, Chongqing 401420, China
    2. Chongqing Key Laboratory of Public Big Data Security Technology, Chongqing 401420, China
  • Received:2025-12-16 Online:2026-01-25 Published:2026-01-28
  • Contact: XIONG Ziyi

摘要:

随着通感一体化技术在未来6G网络中的快速发展,通信与感知功能的深度融合在促使系统性能提升的同时,也引发了多维度的安全挑战。从安全需求角度出发,分析了通感一体化系统在物理层、隐私保护以及传统通信与6G新场景下的复合安全风险。具体而言,物理层安全面临着信道状态伪造、环境反射操控及通信与感知信号联合攻击等威胁;隐私保护方面则需应对用户位置信息、行为轨迹及高维感知数据泄露的风险;同时,系统仍需满足身份认证、数据完整性和低时延交互等基本安全需求。针对上述安全需求,总结了现有关键技术进展,包括射频指纹轻量化认证、深度学习异常检测、差分隐私与联邦学习结合的感知数据保护、深度强化学习驱动的资源调控与联合调度机制,以及基于区块链的分布式信任管理与轻量化边缘协作策略。综合上述技术,可在物理层、数据处理、资源管理及跨域协作等多方面构建系统级安全保障,为通感一体化系统在高动态、高密度和强实时性环境下的安全、可信运行提供理论支持与技术参考。

关键词: 通感一体化, 物理层安全, 隐私保护, 智能化资源分配, 区块链

Abstract:

With the rapid advancement of integrated communication-sensing technology in future 6G networks, the deep integration of communication and sensing functions not only enhances system performance but also introduces multidimensional security challenges. From a security perspective, this paper analyzes the composite security risks of integrated communication-sensing systems at the physical layer, privacy protection, and in traditional communication versus 6G new scenarios. Specifically, physical layer security faces threats such as channel state spoofing, environmental reflection manipulation, and joint attacks on communication and sensing signals. Privacy protection requires addressing risks of user location information leakage, behavioral trajectory exposure, and high-dimensional sensing data breaches. Simultaneously, the system must still meet fundamental security requirements including identity authentication, data integrity, and low-latency interaction. To address these security needs, key technological advancements are summarized, including lightweight RF fingerprint authentication, deep learning-based anomaly detection, perception data protection combining differential privacy and federated learning, resource regulation and joint scheduling mechanisms driven by deep reinforcement learning, as well as blockchain-based distributed trust management and lightweight edge collaboration strategies. By integrating these technologies, system-level security safeguards can be established across multiple dimensions including physical layer, data processing, resource management, and cross-domain collaboration, providing theoretical support and technical references for secure and trustworthy operation of integrated communication-sensing systems in high-dynamic, high-density, and strongly real-time environments.

Key words: intelligent integration, physical layer security, privacy protection, intelligent resource allocation, blockchain

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