Deep Neural Networks Meet CSI-Based Authentication
@article{Abyaneh2018DeepNN, title={Deep Neural Networks Meet CSI-Based Authentication}, author={Amirhossein Yazdani Abyaneh and Ali Hosein Gharari Foumani and V. Pourahmadi}, journal={ArXiv}, year={2018}, volume={abs/1812.04715} }
The first step of a secure communication is authenticating legible users and detecting the malicious ones. [...] Key Method Our approach presents a way of extracting features from raw CSI measurements which are stable towards rotation. We extract these features by the means of a deep neural network. We also present a scenario in which users can be {efficiently} authenticated while they are at certain locations in an environment (even if they rotate); and, they will be rejected if they change their location…Expand
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References
SHOWING 1-10 OF 10 REFERENCES
Authenticating Users Through Fine-Grained Channel Information
- Computer Science
- IEEE Transactions on Mobile Computing
- 2018
- 26
- Highly Influential
- PDF
Broadcasting Into the Uncertainty: Authentication and Confidentiality by Physical-Layer Processing
- Engineering, Computer Science
- Proceedings of the IEEE
- 2015
- 58
Detecting and Localizing Identity-Based Attacks in Wireless and Sensor Networks
- Engineering, Computer Science
- IEEE Transactions on Vehicular Technology
- 2010
- 185
- PDF
Physical layer based authentication without phase detection
- Computer Science
- 2016 50th Asilomar Conference on Signals, Systems and Computers
- 2016
- 5
ProxiMate: proximity-based secure pairing using ambient wireless signals
- Computer Science
- MobiSys '11
- 2011
- 189
- PDF
Deep Learning for Massive MIMO CSI Feedback
- Computer Science, Mathematics
- IEEE Wireless Communications Letters
- 2018
- 222
- PDF
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- Computer Science
- ICML
- 2015
- 21,987
- Highly Influential
- PDF