{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T08:34:10Z","timestamp":1769762050346,"version":"3.49.0"},"reference-count":36,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,2]],"date-time":"2017-11-02T00:00:00Z","timestamp":1509580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61300206"],"award-info":[{"award-number":["61300206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61472098"],"award-info":[{"award-number":["61472098"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["6177010612"],"award-info":[{"award-number":["6177010612"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Device-free passive identity identification attracts much attention in recent years, and it is a representative application in sensorless sensing. It can be used in many applications such as intrusion detection and smart building. Previous studies show the sensing potential of WiFi signals in a device-free passive manner. It is confirmed that human\u2019s gait is unique from each other similar to fingerprint and iris. However, the identification accuracy of existing approaches is not satisfactory in practice. In this paper, we present Wii, a device-free WiFi-based Identity Identification approach utilizing human\u2019s gait based on Channel State Information (CSI) of WiFi signals. Principle Component Analysis (PCA) and low pass filter are applied to remove the noises in the signals. We then extract several entities\u2019 gait features from both time and frequency domain, and select the most effective features according to information gain. Based on these features, Wii realizes stranger recognition through Gaussian Mixture Model (GMM) and identity identification through a Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. It is implemented using commercial WiFi devices and evaluated on a dataset with more than 1500 gait instances collected from eight subjects walking in a room. The results indicate that Wii can effectively recognize strangers and can achieves high identification accuracy with low computational cost. As a result, Wii has the potential to work in typical home security systems.<\/jats:p>","DOI":"10.3390\/s17112520","type":"journal-article","created":{"date-parts":[[2017,11,3]],"date-time":"2017-11-03T04:43:13Z","timestamp":1509684193000},"page":"2520","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Device-Free Passive Identity Identification via WiFi Signals"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5502-7217","authenticated-orcid":false,"given":"Jiguang","family":"Lv","sequence":"first","affiliation":[{"name":"Information Security Research Center, Harbin Engineering University, Harbin 150001, China"}]},{"given":"Wu","family":"Yang","sequence":"additional","affiliation":[{"name":"Information Security Research Center, Harbin Engineering University, Harbin 150001, China"}]},{"given":"Dapeng","family":"Man","sequence":"additional","affiliation":[{"name":"Information Security Research Center, Harbin Engineering University, Harbin 150001, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/0031-3203(95)00106-9","article-title":"Fingerprint Classification","volume":"29","author":"Karu","year":"1996","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1109\/5.381842","article-title":"Human and Machine Recognition of Faces: A Survey","volume":"83","author":"Chellappa","year":"1995","journal-title":"Proc. IEEE"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1016\/j.patrec.2007.05.017","article-title":"Iris Recognition Based on Score Level Fusion by Using SVM","volume":"28","author":"Park","year":"2007","journal-title":"Pattern Recognit. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Niu, J., Wang, B., Cheng, L., and Rodrigues, J.J.P.C. (2015, January 8\u201312). WicLoc: An Indoor Localization System based on WiFi Fingerprints and Crowdsourcing. Proceedings of the IEEE International Conference on Communications (ICC), London, UK.","DOI":"10.1109\/ICC.2015.7248785"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Youssef, M., Mah, M., and Agrawala, A. (2007, January 9\u201314). Challenges: Device-free passive localization for wireless environments. Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking, Montreal, QC, Canada.","DOI":"10.1145\/1287853.1287880"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Pathak, P.H., and Mohapatra, P. (2016, January 11\u201314). WiWho: WiFi-based Person Identification in Smart Spaces. Proceedings of the 15th International Conference on Information Processing in Sensor Networks, Vienna, Austria.","DOI":"10.1109\/IPSN.2016.7460727"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xin, T., Guo, B., Wang, Z., Li, M., Yu, Z., and Zhou, X. (2016, January 4\u20138). FreeSense: Indoor Human Identification with Wi-Fi Signals. Proceedings of the IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA.","DOI":"10.1109\/GLOCOM.2016.7841847"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wei, B., Hu, W., and Kanhere, S.S. (2016, January 26\u201328). WiFi-ID: Human Identification Using WiFi Signal. Proceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS), Washington, DC, USA.","DOI":"10.1109\/DCOSS.2016.30"},{"key":"ref_9","unstructured":"Liam, L.W., Chekima, A., Fan, L.C., and Dargham, J.A. (2002, January 17). Iris Recognition Using Self-Organizing Neural Network. Proceedings of the Student Conference on Research and Development, Shah Alam, Malaysia."},{"key":"ref_10","first-page":"53","article-title":"Iris Texture Analysis and Feature Extraction for Biometric Pattern Recognition","volume":"1","author":"Bhattacharyya","year":"2008","journal-title":"Int. J. Database Theory Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1016\/j.amc.2006.06.082","article-title":"Enhanced Gradient-Based Algorithm for the Estimation of Fingerprint Orientation Fields","volume":"185","author":"Wang","year":"2007","journal-title":"Appl. Math. Comput."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yang, J., Ge, Y., Xiong, H., Chen, Y., and Liu, H. (2010, January 14\u201319). Performing Joint Learning for Passive Intrusion Detection in Pervasive Wireless Environments. Proceedings of the 2010 Proceedings IEEE INFOCOM, San Diego, CA, USA.","DOI":"10.1109\/INFCOM.2010.5462148"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kosba, A.E., Saeed, A., and Youssef, M. (2012, January 19\u201323). RASID: A Robust WLAN Device-Free Passive Motion Detection System. Proceedings of the IEEE International Conference on Pervasive Computing and Communications, Lugano, Switzerland.","DOI":"10.1109\/PerCom.2012.6199865"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"996","DOI":"10.1109\/TPDS.2012.134","article-title":"RASS: A Real-Time, Accurate, and Scalable System for Tracking Transceiver-Free Objects","volume":"24","author":"Zhang","year":"2013","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1109\/JSAC.2015.2430272","article-title":"Occupancy Estimation Using Only WiFi Power Measurements","volume":"33","author":"Depatla","year":"2015","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1145\/1925861.1925870","article-title":"Tool Release: Gathering 802.11 n Traces with Channel State Information","volume":"41","author":"Halperin","year":"2011","journal-title":"ACM SIGCOMM Comput. Commun. Rev."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1007\/s11277-015-2438-7","article-title":"Bfp: Behavior-Free Passive Motion Detection Using PHY Information","volume":"83","author":"Liu","year":"2015","journal-title":"Wirel. Pers. Commun."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Qian, K., Wu, C., Yang, Z., Liu, Y., and Zhou, Z. (2014, January 16\u201319). PADS: Passive Detection of Moving Targets with Dynamic Speed Using PHY Layer Information. Proceedings of the 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS), Hsinchu, Taiwan.","DOI":"10.1109\/PADSW.2014.7097784"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Lv, J., Yang, W., Gong, L., Man, D., and Du, X. (2016, January 4\u20138). Robust WLAN-Based Indoor Fine-Grained Intrusion Detection. Proceedings of the IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA.","DOI":"10.1109\/GLOCOM.2016.7842238"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Domenico, S.D., Sanctis, M.D., Cianca, E., and Bianchi, G. (2016, January 26). A Trained-once Crowd Counting Method Using Differential WiFi Channel State Information. Proceedings of the 3rd International on Workshop on Physical Analytics, Singapore.","DOI":"10.1145\/2935651.2935657"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3837","DOI":"10.1109\/JSEN.2013.2259692","article-title":"Estimating Crowd Density in an RF-Based Dynamic Environment","volume":"13","author":"Yuan","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Domenico, S.D., Pecoraro, G., Cianca, E., and Sanctis, M.D. (2016, January 17\u201319). Trained-Once Device-Free Crowd Counting and Occupancy Estimation Using WiFi: A Doppler Spectrum Based Approach. Proceedings of the 12th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), New York, NY, USA.","DOI":"10.1109\/WiMOB.2016.7763227"},{"key":"ref_23","unstructured":"Xi, W., Zhao, J., Li, X.Y., Zhao, K., Tang, S., Liu, X., and Jiang, Z. (May, January 27). Electronic Frog Eye: Counting Crowd Using WiFi. Proceedings of the IEEE Conference on Computer Communications, Toronto, ON, Canada."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wang, Y., Liu, J., Chen, Y., Gruteser, M., Yang, J., and Liu, H. (2014, January 7\u201311). E-eyes: Device-Free Location-Oriented Activity Identification Using Fine-Grained WiFi Signatures. Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, Maui, HI, USA.","DOI":"10.1145\/2639108.2639143"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wang, W., Liu, A.X., Shahzad, M., Ling, K., and Lu, S. (2015, January 7\u201311). Understanding and Modeling of WiFi Signal Based Human Activity Recognition. Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, Paris, France.","DOI":"10.1145\/2789168.2790093"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Sun, L., Sen, S., Koutsonikolas, D., and Kim, K.-H. (2015, January 7\u201311). WiDraw: Enabling Hands-free Drawing in the Air on Commodity WiFi Devices. Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, Paris, France.","DOI":"10.1145\/2789168.2790129"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zheng, X., Wang, J., Shangguan, L., Zhou, Z., and Liu, Y. (2016, January 10\u201314). Smokey: Ubiquitous Smoking Detection with Commercial WiFi Infrastructures. Proceedings of the 35th Annual IEEE International Conference on Computer Communications, San Francisco, CA, USA.","DOI":"10.1109\/INFOCOM.2016.7524399"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Tan, S., and Yang, J. (2016, January 5\u20138). WiFinger: Leveraging commodity WiFi for fine-grained finger gesture recognition. Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, Paderborn, Germany.","DOI":"10.1145\/2942358.2942393"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2673","DOI":"10.1016\/j.patcog.2014.01.016","article-title":"A review of Biometric Technology Along with Trends and Prospects","volume":"47","author":"Unar","year":"2014","journal-title":"Pattern Recognit."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Wang, W., Liu, A.X., and Shahzad, M. (2016, January 12\u201316). Gait Recognition Using WiFi Signals. Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.","DOI":"10.1145\/2971648.2971670"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2543581.2543592","article-title":"From RSSI to CSI: Indoor Localization via Channel Response","volume":"46","author":"Yang","year":"2013","journal-title":"ACM Comput. Surv."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1671","DOI":"10.1121\/1.406784","article-title":"Ten Lectures on Wavelets","volume":"93","author":"Daubechies","year":"1993","journal-title":"J. Acoust. Soc. Am."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1093\/plankt\/fbv116","article-title":"Using Wavelet Analyses to Examine Variability in Phytoplankton Seasonal Succession and Annual Periodicity","volume":"38","author":"Carey","year":"2016","journal-title":"J. Plankton Res."},{"key":"ref_34","unstructured":"Witten, I.H., Frank, E., and Hall, M.A. (2011). Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann Publishers Inc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A Library for Support Vector Machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1177\/001316446002000104","article-title":"A Coefficient of Agreement for Nominal Scales","volume":"20","author":"Cohen","year":"1960","journal-title":"Educ. Psychol. Meas."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2520\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:47:55Z","timestamp":1760208475000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2520"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,2]]},"references-count":36,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2017,11]]}},"alternative-id":["s17112520"],"URL":"https:\/\/doi.org\/10.3390\/s17112520","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,2]]}}}