Wearable Device Bluetooth/BLE Physical Layer Dataset
Author:
Affiliation:
1. Institute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, Latvia
2. Institute of Mathematics and Computer Science, University of Latvia, Raina Blvd. 29, LV-1006 Riga, Latvia
Abstract
Funder
Latvian Council of Science
Publisher
MDPI AG
Link
https://www.mdpi.com/2306-5729/9/4/53/pdf
Reference18 articles.
1. Givehchian, H., Bhaskar, N., Herrera, E.R., Soto, H.R.L., Dameff, C., Bharadia, D., and Schulman, A. (2022, January 22–26). Evaluating physical-layer ble location tracking attacks on mobile devices. Proceedings of the 2022 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA.
2. Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth;Jagannath;IEEE Trans. Cogn. Commun. Netw.,2023
3. Jagannath, A., Kane, Z., and Jagannath, J. (2022, January 4–8). RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth. Proceedings of the IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil.
4. Takanen, A., DeMott, J., Miller, C., and Kettunen, A. (2018). Fuzzing for Software Security Testing and Quality Assurance Second Edition, Artech House.
5. (2024, January 08). Great Scott Gadgets. Ubertooth One. Available online: https://ubertooth.readthedocs.io/en/latest/ubertooth_one.html.
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