Além do Sinal: Autenticação Biofísica com Wi-Fi CSI e Raspberry Pi
Resumo
O Channel State Information (CSI) do Wi-Fi tem sido amplamente estudado em atividades de sensoriamento. No entanto, implementações práticas voltadas à autenticação de pessoas são pouco exploradas. Este estudo propõe o uso de dispositivos Raspberry Pi para coleta dados de CSI em um ambiente controlado e aplica aprendizado supervisionado para reconhecer características biofísicas e comportamentais visando controle de acesso físico. A pesquisa também explora o uso dos filtros de Hampel e Savitzky-Golay (SG) no pré-processamento dos dados e compara o desempenho de algoritmos de classificação, com destaque para o K-Nearest Neighbors (KNN), alcançando 99,92% de precisão na autenticação de usuários.
Referências
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Chen, C., Song, H., Li, Q., Meneghello, F., Restuccia, F., and Cordeiro, C. (2023). Wi-fi sensing based on ieee 802.11bf. IEEE Communications Magazine, 61(1):121–127.
Chen, Z., Zhang, L., Jiang, C., Cao, Z., and Cui, W. (2019). Wifi csi based passive human activity recognition using attention based blstm. IEEE Transactions on Mobile Computing, 18(11):2714–2724.
Cheng, X., Huang, B., and Zong, J. (2021). Device-free human activity recognition based on gmm-hmm using channel state information. IEEE Access, 9:76592–76601.
Ding, J. and Wang, Y. (2019). Wifi csi-based human activity recognition using deep recurrent neural network. IEEE Access, 7:174257–174269.
Galdino, I., Soto, J. C. H., Caballero, E., Ferreira, V., Ramos, T. C., Albuquerque, C., and Muchaluat-Saade, D. C. (2023). ehealth csi: A wi-fi csi dataset of human activities. IEEE Access, 11:71003–71012.
Gringoli, F., Schulz, M., Link, J., and Hollick, M. (2019). Free your csi: A channel state information extraction platform for modern wi-fi chipsets. WiNTECH ’19, page 2128, New York, NY, USA. Association for Computing Machinery.
Gu, Y., Wang, Y., Wang, M., Pan, Z., Hu, Z., Liu, Z., Shi, F., and Dong, M. (2022). Secure user authentication leveraging keystroke dynamics via wi-fi sensing. IEEE Transactions on Industrial Informatics, 18(4):2784–2795.
Gu, Y., Yan, H., Dong, M., Wang, M., Zhang, X., Liu, Z., and Ren, F. (2021). Wione: One-shot learning for environment-robust device-free user authentication via commodity wi-fi in manmachine system. IEEE Transactions on Computational Social Systems, 8(3):630–642.
Guo, L., Wang, L., Liu, J., Zhou, W., Liu, B. L. T., Li, G., and Li, C. (2017). A novel benchmark on human activity recognition using wifi signals. In 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom), pages 1–6.
Handa, J., Singh, A., Goyal, A., and Aggarwal, P. (2018). Behavioral biometrics for continuous authentication. In 2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC), pages 284–289.
Kong, H., Lu, L., Yu, J., Chen, Y., Xu, X., Tang, F., and Chen, Y.-C. (2021). Multiauth: Enable multi-user authentication with single commodity wifi device. MobiHoc ’21, page 3140, New York, NY, USA. Association for Computing Machinery.
Lee, W.-H. and Lee, R. B. (2017). Sensor-based implicit authentication of smartphone users. In 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pages 309–320, Denver, CO, USA.
Lin, C., Hu, J., Sun, Y., Ma, F., Wang, L., and Wu, G. (2018). Wiau: An accurate device-free authentication system with resnet. In 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pages 1–9.
Ma, Y., Zhou, G., and Wang, S. (2019). Wifi sensing with channel state information: A survey. ACM Comput. Surv., 52(3).
Ma, Y., Zhou, G., Wang, S., Zhao, H., and Jung, W. (2018). Signfi: Sign language recognition using wifi. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2(1).
Meneghello, F., Garlisi, D., Fabbro, N. D., Tinnirello, I., and Rossi, M. (2023). Sharp: Environment and person independent activity recognition with commodity ieee 802.11 access points. IEEE Transactions on Mobile Computing, 22(10):6160–6175.
Niu, K., Zhang, F., Chang, Z., and Zhang, D. (2018). A fresnel diffraction model based human respiration detection system using cots wi-fi devices. UbiComp ’18. Association for Computing Machinery.
Ren, S., Wang, H., Gong, L., Xiang, C., Wu, X., and Du, Y. (2019). Intelligent contactless gesture recognition using wlan physical layer information. IEEE Access, 7:92758–92767.
Shah, S. W. and Kanhere, S. S. (2017). Wi-auth: Wifi based second factor user authentication. MobiQuitous 2017, page 393402, New York, NY, USA. Association for Computing Machinery.
Shahzad, M., Liu, A. X., and Samuel, A. (2013). Secure unlocking of mobile touch screen devices by simple gestures: You can see it but you can not do it. MobiCom ’13, pages 39–50, New York, NY, USA. Association for Computing Machinery.
Soto, J. C. H., Galdino, I., Caballero, E., Muchaluat-Saade, D., and Albuquerque, C. (2023). Single person identification using wi-fi signals. In 2023 IEEE Latin-American Conference on Communications (LATINCOM), pages 1–6.
Tan, S. and Yang, J. (2016). Wifinger: leveraging commodity wifi for fine-grained finger gesture recognition. In Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 201–210.
Tian, Z., Wang, J., Yang, X., and Zhou, M. (2018). Wicatch: A wi-fi based hand gesture recognition system. IEEE Access, 6:16911–16923.
Wang, W., Liu, A. X., and Shahzad, M. (2016). Gait recognition using wifi signals. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp ’16, page 363373, New York, NY, USA. Association for Computing Machinery.
Wang, Z., Jiang, K., Hou, Y., Dou, W., Zhang, C., Huang, Z., and Guo, Y. (2019). A survey on human behavior recognition using channel state information. IEEE Access, 7:155986–156024.
Wu, D., Zhang, D., Xu, C., Wang, H., and Li, X. (2017). Device-free wifi human sensing: From pattern-based to model-based approaches. IEEE Communications Magazine, 55(10):91–97.
Yousefi, S., Narui, H., Dayal, S., Ermon, S., and Valaee, S. (2017). A survey on behavior recognition using wifi channel state information. IEEE Communications Magazine, 55(10):98–104.
Zhang, D., Wang, H., and Wu, D. (2017). Toward centimeter-scale human activity sensing with wi-fi signals. Computer Society, 50(1):48–57.
Zhang, F., Niu, K., Xiong, J., Jin, B., Gu, T., Jiang, Y., and Zhang, D. (2019). Towards a diffraction-based sensing approach on human activity recognition. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 3(1).
Zhang, Y., Zheng, Y., Zhang, G., Qian, K., Qian, C., and Yang, Z. (2020). Gaitid: Robust wi-fi based gait recognition. In Wireless Algorithms, Systems, and Applications: 15th International Conference, WASA 2020, Qingdao, China, September 13–15, 2020, Proceedings, Part I 15.
Zhao, Y., Gao, R., Liu, S., Xie, L., Wu, J., Tu, H., and Chen, B. (2021). Device-free secure interaction with hand gestures in wifi-enabled iot environment. IEEE Internet of Things Journal, 8(7):5619–5631.
Zou, H., Zhou, Y., Yang, J., Jiang, H., Xie, L., and Spanos, C. J. (2018). Deepsense: Device-free human activity recognition via autoencoder long-term recurrent convolutional network. In 2018 IEEE International Conference on Communications (ICC), pages 1–6.
Chen, C., Song, H., Li, Q., Meneghello, F., Restuccia, F., and Cordeiro, C. (2023). Wi-fi sensing based on ieee 802.11bf. IEEE Communications Magazine, 61(1):121–127.
Chen, Z., Zhang, L., Jiang, C., Cao, Z., and Cui, W. (2019). Wifi csi based passive human activity recognition using attention based blstm. IEEE Transactions on Mobile Computing, 18(11):2714–2724.
Cheng, X., Huang, B., and Zong, J. (2021). Device-free human activity recognition based on gmm-hmm using channel state information. IEEE Access, 9:76592–76601.
Ding, J. and Wang, Y. (2019). Wifi csi-based human activity recognition using deep recurrent neural network. IEEE Access, 7:174257–174269.
Galdino, I., Soto, J. C. H., Caballero, E., Ferreira, V., Ramos, T. C., Albuquerque, C., and Muchaluat-Saade, D. C. (2023). ehealth csi: A wi-fi csi dataset of human activities. IEEE Access, 11:71003–71012.
Gringoli, F., Schulz, M., Link, J., and Hollick, M. (2019). Free your csi: A channel state information extraction platform for modern wi-fi chipsets. WiNTECH ’19, page 2128, New York, NY, USA. Association for Computing Machinery.
Gu, Y., Wang, Y., Wang, M., Pan, Z., Hu, Z., Liu, Z., Shi, F., and Dong, M. (2022). Secure user authentication leveraging keystroke dynamics via wi-fi sensing. IEEE Transactions on Industrial Informatics, 18(4):2784–2795.
Gu, Y., Yan, H., Dong, M., Wang, M., Zhang, X., Liu, Z., and Ren, F. (2021). Wione: One-shot learning for environment-robust device-free user authentication via commodity wi-fi in manmachine system. IEEE Transactions on Computational Social Systems, 8(3):630–642.
Guo, L., Wang, L., Liu, J., Zhou, W., Liu, B. L. T., Li, G., and Li, C. (2017). A novel benchmark on human activity recognition using wifi signals. In 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom), pages 1–6.
Handa, J., Singh, A., Goyal, A., and Aggarwal, P. (2018). Behavioral biometrics for continuous authentication. In 2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC), pages 284–289.
Kong, H., Lu, L., Yu, J., Chen, Y., Xu, X., Tang, F., and Chen, Y.-C. (2021). Multiauth: Enable multi-user authentication with single commodity wifi device. MobiHoc ’21, page 3140, New York, NY, USA. Association for Computing Machinery.
Lee, W.-H. and Lee, R. B. (2017). Sensor-based implicit authentication of smartphone users. In 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pages 309–320, Denver, CO, USA.
Lin, C., Hu, J., Sun, Y., Ma, F., Wang, L., and Wu, G. (2018). Wiau: An accurate device-free authentication system with resnet. In 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pages 1–9.
Ma, Y., Zhou, G., and Wang, S. (2019). Wifi sensing with channel state information: A survey. ACM Comput. Surv., 52(3).
Ma, Y., Zhou, G., Wang, S., Zhao, H., and Jung, W. (2018). Signfi: Sign language recognition using wifi. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2(1).
Meneghello, F., Garlisi, D., Fabbro, N. D., Tinnirello, I., and Rossi, M. (2023). Sharp: Environment and person independent activity recognition with commodity ieee 802.11 access points. IEEE Transactions on Mobile Computing, 22(10):6160–6175.
Niu, K., Zhang, F., Chang, Z., and Zhang, D. (2018). A fresnel diffraction model based human respiration detection system using cots wi-fi devices. UbiComp ’18. Association for Computing Machinery.
Ren, S., Wang, H., Gong, L., Xiang, C., Wu, X., and Du, Y. (2019). Intelligent contactless gesture recognition using wlan physical layer information. IEEE Access, 7:92758–92767.
Shah, S. W. and Kanhere, S. S. (2017). Wi-auth: Wifi based second factor user authentication. MobiQuitous 2017, page 393402, New York, NY, USA. Association for Computing Machinery.
Shahzad, M., Liu, A. X., and Samuel, A. (2013). Secure unlocking of mobile touch screen devices by simple gestures: You can see it but you can not do it. MobiCom ’13, pages 39–50, New York, NY, USA. Association for Computing Machinery.
Soto, J. C. H., Galdino, I., Caballero, E., Muchaluat-Saade, D., and Albuquerque, C. (2023). Single person identification using wi-fi signals. In 2023 IEEE Latin-American Conference on Communications (LATINCOM), pages 1–6.
Tan, S. and Yang, J. (2016). Wifinger: leveraging commodity wifi for fine-grained finger gesture recognition. In Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 201–210.
Tian, Z., Wang, J., Yang, X., and Zhou, M. (2018). Wicatch: A wi-fi based hand gesture recognition system. IEEE Access, 6:16911–16923.
Wang, W., Liu, A. X., and Shahzad, M. (2016). Gait recognition using wifi signals. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp ’16, page 363373, New York, NY, USA. Association for Computing Machinery.
Wang, Z., Jiang, K., Hou, Y., Dou, W., Zhang, C., Huang, Z., and Guo, Y. (2019). A survey on human behavior recognition using channel state information. IEEE Access, 7:155986–156024.
Wu, D., Zhang, D., Xu, C., Wang, H., and Li, X. (2017). Device-free wifi human sensing: From pattern-based to model-based approaches. IEEE Communications Magazine, 55(10):91–97.
Yousefi, S., Narui, H., Dayal, S., Ermon, S., and Valaee, S. (2017). A survey on behavior recognition using wifi channel state information. IEEE Communications Magazine, 55(10):98–104.
Zhang, D., Wang, H., and Wu, D. (2017). Toward centimeter-scale human activity sensing with wi-fi signals. Computer Society, 50(1):48–57.
Zhang, F., Niu, K., Xiong, J., Jin, B., Gu, T., Jiang, Y., and Zhang, D. (2019). Towards a diffraction-based sensing approach on human activity recognition. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 3(1).
Zhang, Y., Zheng, Y., Zhang, G., Qian, K., Qian, C., and Yang, Z. (2020). Gaitid: Robust wi-fi based gait recognition. In Wireless Algorithms, Systems, and Applications: 15th International Conference, WASA 2020, Qingdao, China, September 13–15, 2020, Proceedings, Part I 15.
Zhao, Y., Gao, R., Liu, S., Xie, L., Wu, J., Tu, H., and Chen, B. (2021). Device-free secure interaction with hand gestures in wifi-enabled iot environment. IEEE Internet of Things Journal, 8(7):5619–5631.
Zou, H., Zhou, Y., Yang, J., Jiang, H., Xie, L., and Spanos, C. J. (2018). Deepsense: Device-free human activity recognition via autoencoder long-term recurrent convolutional network. In 2018 IEEE International Conference on Communications (ICC), pages 1–6.
Publicado
13/09/2024
Como Citar
TRINDADE, Eduardo Fabrício Gomes; ALMEIDA, Felipe Silveira de; PEREIRA JUNIOR, Lourenço Alves.
Além do Sinal: Autenticação Biofísica com Wi-Fi CSI e Raspberry Pi. In: SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 24. , 2024, São José dos Campos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 32-47.
DOI: https://doi.org/10.5753/sbseg.2024.241787.
