Netinfo Security ›› 2026, Vol. 26 ›› Issue (10): 1497-1525.doi: 10.3969/j.issn.1671-1122.2026.10.001
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Li Guyue(
), Xu Xiaoyu, Chu Zhiming
Received:2026-05-20
Online:2026-10-10
Published:2026-11-06
Contact:
Li Guyue
E-mail:guyuelee@seu.edu.cn
CLC Number:
Li Guyue, Xu Xiaoyu, Chu Zhiming. RF-based wireless sensing security: evolution, threats and defense[J]. Netinfo Security, 2026, 26(10): 1497-1525.
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URL: http://netinfo-security.org/EN/10.3969/j.issn.1671-1122.2026.10.001
| 平台 | 频段 | 感知范围 | 时延 | 功耗 | 适用感知任务 |
|---|---|---|---|---|---|
| 蜂窝 | 450 MHz~ 1 THz(预期) | 数百米 | 1~10 ms | 中等 | 支持亚厘米级定位、微动识别 |
| Wi-Fi | 2.4/5/6 GHz | 数十米 | 1~10 ms | 中高 | 支持高精度定位、 动作识别、健康监测 |
| RFID | 低频:125~134 kHz 高频:13 MHz | 约10米 | 小于1 s | 极低 | 支持近距离定位、 目标识别与运动追踪 |
| LoRa | 433/868/ 915 MHz | 城市约2 km,郊区约10 km | 较长 | 极低 | 支持粗定位、目标检测,传输速率偏低,不适合复杂的感知 需求 |
| 毫米波雷达 | 60/77 GHz | 数百米 | 小于1 ms | 中等 | 支持高精度定位、 速度与角度测量、 目标追踪及动作识别 |
| 分类 | 感知方法 | 适配平台 | 依赖特征 | 典型算法 | 代表性性能 指标 |
|---|---|---|---|---|---|
| 模型驱动 | 几何模型法 | Wi-Fi、RFID、LoRa、蜂窝、毫米波雷达 | RSSI、CSI | 几何运动学 模型Widar[ | 定位误差为0.24 m |
| 菲涅尔区 理论[ | 呼吸误差小于0.5 bpm | ||||
| 信号处理 方法 | Wi-Fi、蜂窝、毫米波雷达 | CSI | DWT WiFinger[ | 手势识别误差为0.4% | |
| MUSIC SpotFi[ | 定位误差为0.4 m | ||||
| ISAC联合 优化 | 5G/6G蜂窝 | — | 文献[ | 速度估计 误差为0.1 m/s | |
| 数据驱动 | 通用深度 学习 | Wi-Fi、蜂窝 | CSI、 BFI | CNN+LSTM[ | 行为识别准确率为85% |
| LSTM[ | 人类活动 识别准确率为90% | ||||
| 多节点协同感知 | 多天线 Wi-Fi、分布式蜂窝基站 | CSI | AdaWiFi[ | 行为识别准确率为88.5% | |
| CREWS[ | 行为识别准确率为96% | ||||
| 跨域泛化与鲁棒算法 | Wi-Fi、蜂窝、毫米波雷达 | — | 自监督对比学习AutoFi[ | 泛化准确率为86.8% | |
| 少样本学习BeamSense[ | 泛化准确率为 90%~95% |
| 分类 | 涉及无线 感知平台 | 工作举例 | 核心原理 | 挑战 | |
|---|---|---|---|---|---|
| 被动攻击:无线感知系统的隐私 泄露 | 基于辐射泄露的敏感信息 窃取 | RFID、LoRa | SpiderMon[ | 监听设备运行过程中泄露的电磁辐射并恢复 信息 | 高采样率设备; 环境噪声剥离 |
| 基于通信协议特征的语义 推断 | Wi-Fi、 蜂窝 | WiFiLeaks[ | 监听通信协议信号,推断用户行为 | 语义标注成本高; 依赖连续采样流 | |
| 主动攻击:无线感知系统的干扰 对抗 | 基于模型对抗的对抗样本 构造 | Wi-Fi:伪造CSI或BFI; 蜂窝:伪造同步导频 | 白盒:Wi-Spoof[ 黑盒:MadRadar[ | 针对机器学习模型,向无线感知特征注入微小扰动,诱导模型误报 | 白盒攻击需要掌握模型参数; 黑盒攻击需获取查询接口; 平衡攻击性能与隐蔽性 |
| 基于信号注入的无线感知结果篡改 | RFID:干扰读写器使其无法获取标签回波; 毫米波雷达、Wi-Fi:改变信道 环境 | 信号欺骗:mmSpoof[ 信道操控:MmVanish[ | 针对感知源,主动伪造或重放信号;针对信道,主动改变信道环境加以干预 | 需要专用信号发射设备,如反射阵列; 需要考虑复杂的多径环境与信号同步 | |
| 分类 | 涉及无线感知平台 | 工作举例 | 核心原理 | 挑战 | |
|---|---|---|---|---|---|
| 无线感知系统的隐私保护 机制 | 面向侧信道掩盖的信号混淆机制 | RFID、LoRa: 轻量级信号扰动 | IRShield[ | 利用波束成形等手段在信号源或信道层面对信号进行处理与重构,抑制敏感特征 | 平衡隐私保护与无线感知性能; 低功耗无源设备如何实现对抗计算 |
| 隐私保护的人工伪造帧注入机制 | Wi-Fi: 波束定向屏蔽、物理层加密; 蜂窝: 添加人工 响应 | PhyCloak[ | 在感知发射端引入人工噪声和随机化设计 | 如何在保障细粒度无线感知的条件下,防止特征被第三方恶意解耦 | |
| 无线感知系统的鲁棒增强 机制 | 基于无线感知模型免疫的防对抗 加固 | Wi-Fi、 蜂窝 | 对抗训练RMBN[ | 通过输入数据噪声平滑、模型梯度掩盖,增强深度学习无线感知模型的鲁棒性 | 对抗训练训练成本高; 泛化性有限 |
| 基于信号认证的信号真实性检验 | Wi-Fi:干扰检测与抑制; 毫米波雷达:上下文协同防御 | 干扰检测与抑制iSense[ | 通过异常信号阈值检测、多节点协同校验,甄别伪造、篡改、恶意注入的信号 | 高精度认证增加计算 开销; 自然多径变化与恶意操控难以区分 | |
| 防御策略类别 | 核心抗攻击类型 | 适用平台 | 典型防御 方法 | 典型防御效果 | 计算开销 |
|---|---|---|---|---|---|
| 信号混淆与掩蔽 | 设备 泄露、 被动监听 | Wi-Fi、蜂窝 | IRShield[ | 窃听率降至5% | 其中,N为RIS的反射单元总数,T为配置更新频率 |
| Protego[ | 窃听率降至25% | ||||
| 人工伪造帧注入与防护 | 隐私窃取、细粒度击键窃听 | Wi-Fi、蜂窝、毫米波雷达 | Secur-Fi[ | 窃听率降至28% | 其中,M为网卡天线通道数,N为子载波数 |
| PhyCloak[ | 攻击效果降至15% | N为信号采样点数 | |||
| 对抗训练与鲁棒 模型 | 对抗样本攻击 | Wi-Fi、 蜂窝 | RMBN[ | 面对攻击识别准确率恢复至85% | 其中,I为迭代次数,K为批量大小,D为网络参数维度 |
| 物理层认证与检验 | 信号注入、伪造欺骗、身份冒充 | Wi-Fi、RFID、LoRa、 蜂窝 | PHYAlert[ | 检测成功率98% | 其中, M为接收端天线数, N为子载波数 |
| RelayShield[ | 检测准确率95% | ||||
| 信道状态一致性 检测 | 伪造帧注入、中间人篡改 | RFID、LoRa、毫米波雷达 | iSense[ | 面对攻击识别准确率恢复至98.6% | N为单帧雷达信号的采样 点数 |
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