Acknowledgement
This was supported by Korea National University of Transportation in 2021.
References
- H. Han and D. Park, "Cybersecurity of The Defense Information System network connected IoT Sensors," Journal of the Korea Institute of Information and Communication Engineering, vol. 24, no. 6, pp. 802-808, Jun. 2020. DOI: 10.6109/jkiice.2020.24.6.802.
- F. D. Garcia, D. Oswald, T. Kasper, and P. Pavlides, "Lock it and still lose it-on the (in)security of automotive remote keyless entry systems," in Proceeding of 25th USENIX security symposium, Austin: TX, USA, pp. 929-944, 2016.
- O. Ureten and N. Serinken. "Wireless security through RF fingerprinting," Canadian Journal of Electrical and Computer Engineering, vol. 32, no. 1, pp. 27-33, 2007. DOI: 10.1109/CJECE.2007.364330.
- B. Danev, T. S. Heydt-Benjamin, and S. Capkun, "Physical-layer identification of RFID devices," in Proceeding of USENIX security symposium, Montreal: QC, Canada, Aug. 2009.
- A. M. Ali, E. Uzundurukan, and A. Kara, "Assessment of Features and Classifiers for Bluetooth RF Fingerprinting," IEEE Access, vol. 7, pp. 50524-50535, Apr. 2019. DOI: 10.1109/ACCESS.2019.2911452.
- K. Merchant, S. Revay, G. Stantchev, and B. Nousain "Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks," IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 1, pp. 160-167, Feb. 2018. DOI: 10.1109/JSTSP.2018.2796446.
- J. Yu, A. Hu, G. Li, and L. Peng, "A Robust RF Fingerprinting Approach Using Multisampling Convolutional Neural Network," IEEE Internet of Things Journal, vol. 6, no. 4, pp. 6486-6799, Aug. 2019. DOI: 10.1109/JIOT.2019.2911347.
- S. Wang, L. Peng, H. Fu, A. Hu, and X. Zhou, "A Convolutional Neural Network-Based RF Fingerprinting Identification Scheme for Mobile Phones," in Proceeding of the IEEE International Conference on Computer Communications, Toronto: ON, Canada, Jul. 2020. DOI: 10.1109/INFOCOMWKSHPS50562.2020.9163058.
- T. Jian, B. C. Rendon, E. Ojuba, N. Wang, K. Sankhe, A. Gritsenko, J. Dy, K. Chowdhury, and S. Ioannidis, "Deep Learning for RF Fingerprinting: A Massive Experimental Study," IEEE Internet of Things Magazine, vol. 3, no. 1, pp. 50-57, Mar. 2020. DOI: 10.1109/IOTM.0001.1900065.
- W. Lee, S. Y. Baek, and S. H. Kim, "Deep-Learning-Aided RF Fingerprinting for NFC Security," IEEE Communications Magazine, vol. 59, no. 5, pp. 96-101, May 2021. DOI: 10.1109/MCOM.001.2000912.
- Y. M. Kim, Y. M. Bak, W. Lee, and S. H. Kim, "Authentication Mechanism for 433MHz band Transceiver Module using Deep learning based RF Fingerprinting," in Proceedings of the 2019 Fall Conference of the Korea Information and Communications, Busan, Korea, pp. 397-399, 2019.
- Y. M. Kim, "Physical-layer schemes to enhance the reliability of authentication for IoT devices," M. S. thesis, Gyeongsang National University, Korea, 2020.
- I. J. Goodfellow, Y. Bengio, and A. Courville, Deep Learning, MIT Press, MA: USA, 2016.