Smart Home Recognition Based on WiFi Data Frame Features

doi:10.3778/j.issn.1002-8331.2205-0574

Abstract

Abstract: The identification of smart home device under WiFi environment is one of the current research hotspots of IoT security. Due to the encryption characteristics of the 802.11 protocol, the characteristics of traditional unencrypted traffic to identify IoT devices cannot be applied. Based on the analysis of 802.11 protocol, it is found that the data frames of diverse smart home devices have different characteristics. In this paper, protocol field such as frame length, frame arrival time, duration, and frame sequence number are selected as traffic characteristics. Through the improved decision tree CART algorithm realize the identification of smart home devices in the WiFi environment. The experimental results show that this method can effectively identify the device model, and the accuracy of recognition is 91.3%.

Key words: smart home, WiFi data frame, traffic characteristics, device identification, machine learning

摘要： WiFi环境下的智能家居设备识别是当前物联网安全的研究热点之一。由于WiFi环境下802.11协议具有加密的特性，使得传统明文流量识别物联网设备的特征无法适用。分析802.11协议发现不同智能家居设备的数据帧存在差异性的特点，基于此开展研究工作，选取帧长度、帧到达时间、持续时间、帧序列号等字段作为流量特征，通过改进的决策树CART算法，实现WiFi环境下智能家居设备识别。实验结果表明该方法能有效识别设备型号，识别准确率为91.3%。

关键词: 智能家居, WiFi数据帧, 流量特征, 设备识别, 机器学习

LIU Dandan, HAN Yi, LIU Xiangyu, XIE Rongrong, WANG Jingxiang, DU Yanhui. Smart Home Recognition Based on WiFi Data Frame Features[J]. Computer Engineering and Applications, 2023, 59(15): 274-280.

刘丹丹, 韩奕, 刘翔宇, 谢镕镕, 王靖翔, 杜彦辉. 基于WiFi数据帧特征的智能家居识别方法[J]. 计算机工程与应用, 2023, 59(15): 274-280.

References

[1] TAHAEI H，AFIFI F，ASEMI A，et al.The rise of traffic classification in IoT networks：a survey[J].Journal of Network and Computer Applications，2020，154（1）：102538-102558.
[2] HOWELL J.Number of connected iot devices will surge to 125 billion by 2030[EB/OL].（2018-11-07）[2020-06-16].http：//technology.ihs.com/596542/.
[3] MIETTINEN M，MARCHAL S，HAFEEZ I，et al.IoT sentinel demo：automated device-type identification for security enforcement in IoT[C]//2017 IEEE 37th International Conference on Distributed Computing Systems（ICDCS），Atlanta，GA，USA，Jun 5-8，2017.Atlanta：IEEE，2017：2511-2514.
[4] HAMAD S A，ZHANG W E，SHENG Q Z，et al.Iot device identification via network-flow based fingerprinting and learning[C]//2019 18th IEEE International Conference on Trust，Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering（TrustCom/BigDataSE），2019：103-111.
[5] CACHE J.Fingerprinting 802.11 implementations via statistical analysis of the duration field[J].Uninformed，2006（5）.
[6] PANG J，GREENSTEIN B，GUMMADI R，et al.11 user fingerprinting[C]//Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking，2007：99-110.
[7] DESMOND L C C，YUAN C C，PHENG T C，et al.Identifying unique devices through wireless fingerprinting[C]//Proceedings of the First ACM Conference on Wireless Network Security，2008：46-55.
[8] NEUMANN C，HEEN O，ONNO S.An empirical study of passive 802.11 device fingerprinting[C]//2012 32nd International Conference on Distribute Computing Systems Workshops，2012：593-602.
[9] 刘玉洁，李娜，姚晓，等.基于802.11帧的无线设备指纹生成方法[J].网络空间安全，2020，11（8）：103-108.
LIU Y J，LI N，YAO X，et al.Generating fingerprint for wireless device based on 802.11 frames[J].Cyberspace Security，2020，11（8）：103-108.
[10] 陈庆港.基于流量特征的物联网设备识别技术研究[D].北京：中国人民公安大学，2022.
CHEN Q G.Research on device identification technology of internet of things based on traffic characteristics[D].Beijing：People’s Public Security University of China，2022.
[11] BRUHADESHWAR B，MAALVIKA B，JORDAN P，et al.IoTSense：behavioral fingerprinting of IoT devices[J].arXiv：1804.03852，2018.
[12] AKSOY A，GUNES M H.Automated iot device identification using network traffic[C]//2019 IEEE International Conference on Communications（ICC），2019：1-7.
[13] PINHEIRO A J，BEZERRA J M，BURGARDT C A P，et al.Identifying IoT devices and events based on packet length from encrypted traffic[J].Computer Communications，2019，144：8-17.
[14] ORTIZ J，CRAWFORD C，LE F.DeviceMien：network device behavior modeling for identifying unknown IoT devices[C]//Proceedings of the International Conference on Internet of Things Design and Implementation，2019：106-117.
[15] ACAR A，FEREIDOONI H，ABERA T，et al.Peek-a-boo：I see your smart home activities，even encrypted![C]//Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks，2020：207-218.
[16] 徐超，王纪军，吴小虎，等.一种基于流量指纹的物联网设备实时自动检测及识别[J].信息安全研究，2021，7（6）：543-549.
XU C，WANG J J，WU X H，et al.Real-time automatic detection and recognition of internet of things equipment based on flow fingerprint[J].Journal of Information Security Research，2021，7（6）：543-549.