基于双模态融合的ZigBee设备识别方法  

A dual-modal fusion approach for ZigBee device identification

作　　者：李荣 赖怡聪 李乐言 Li Rong;Lai Yicong;Li Leyan(China Electronic Product Reliability and Environmental Testing Research Institute,Guangzhou 510610,China)

机构地区：[1]中国电子产品可靠性与环境试验研究所,广东广州510610

出　　处：《网络安全与数据治理》2025年第2期17-25,共9页CYBER SECURITY AND DATA GOVERNANCE

摘　　要：智能家居为人们日常生活带来便利的同时,也带来了隐私安全风险,智能传感器能够不断收集周围环境的信息,并通过无线通信远程传输数据。为了保护用户的隐私安全,提出了一种基于双模态融合的ZigBee设备识别方法。首先,通过空中接口被动捕获智能家居设备ZigBee流量数据;然后,对设备流量进行分片处理,在文本模态下提取加密流量的时序、长度等特征信息,在图像模态下提取流量图像的高维特征;最后,融合加密流量的文本特征和图像特征,构建基于双模态融合的设备类型识别模型。通过对5个厂家15个设备的实验结果表明,即使设备的无线流量被加密保护,该方法在ZigBee设备识别准确率上达到99%左右,能够有效地识别用户身边的智能传感器,保护用户的隐私安全。Smart homes bring convenience to daily life but also introduce privacy and security risks.Smart sensors continuously collect information about their surroundings and transmit data remotely via wireless communication.To protect user privacy,this paper proposes a ZigBee device identification method based on dual-mode fusion.Firstly,ZigBee traffic data from smart home devices is passively captured through the air interface.Then,the device traffic is fragmented:in the text modality,features such as timing and length of encrypted traffic are extracted,while in the image modality,high-dimensional features of traffic images are obtained.Finally,the textual and image features of the encrypted traffic are fused to construct a device type recognition model based on bimodal fusion.Experimental results involving 15 devices from 5 manufacturers show that,even with encrypted wireless traffic,this method achieves an identification accuracy of approximately 99%for ZigBee devices,which can effectively identify nearby smart sensors and protect user privacy.

关 键 词：隐私安全 ZIGBEE 深度学习 智能家居 

分 类 号：TN918[电子电信—通信与信息系统] TP309[电子电信—信息与通信工程]