| Title | A Novel Physical Layer Authentication Method with Convolutional Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Liao, Runfa, Wen, Hong, Pan, Fei, Song, Huanhuan, Xu, Aidong, Jiang, Yixin |
| Conference Name | 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) |
| Keywords | Artificial neural networks, authentication, authentication accuracy, channel authentication, channel state information, CNN, convolution, convolutional neural nets, convolutional neural network, convolutional neural networks, convolutional-neural-network-based approach, CSI, cyber physical systems, hypothesis test based methods, L1 regularization, MIMO communication, MIMO-OFDM, MIMO-OFDM system security, mini batch scheme, multi-access systems, Multi-user, multiple-input multiple-output system, multiuser authentication system, OFDM, OFDM modulation, orthogonal frequency division multiplexing, physical layer authentication method, physical layer security, policy-based governance, pubcrawl, radio transmitters, Resiliency, spoofing attacks, telecommunication security, Wireless communication, wireless networks |
| Abstract | This paper investigates the physical layer (PHY-layer) authentication that exploits channel state information (CSI) to enhance multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system security by detecting spoofing attacks in wireless networks. A multi-user authentication system is proposed using convolutional neural networks (CNNs) which also can distinguish spoofers effectively. In addition, the mini batch scheme is used to train the neural networks and accelerate the training speed. Meanwhile, L1 regularization is adopted to prevent over-fitting and improve the authentication accuracy. The convolutional-neural-network-based (CNN-based) approach can authenticate legitimate users and detect attackers by CSIs with higher performances comparing to traditional hypothesis test based methods. |
| DOI | 10.1109/ICAICA.2019.8873460 |
| Citation Key | liao_novel_2019 |
A Novel Physical Layer Authentication Method with Convolutional Neural Network