KeyAtNet: Keystroke Signal Real-time Eavesdropping Based on Fourier Neural Operator

Author:

Lee Seng-Hong,Yu ZiXun,Chen KeKe,Li Xiao

Publisher

Springer Nature Singapore

Reference11 articles.

1. Asonov, D., Agrawal, R.: Keyboard acoustic emanations. In: Proceedings of the IEEE Symposium on Security and Privacy, pp. 3–11. IEEE (2004)

2. Chollet, F.: Xception: deep learning with depthwise separable convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1251–1258 (2017)

3. Dai, Z., Liu, H., Le, Q.V., Tan, M.: Coatnet: marrying convolution and attention for all data sizes. Adv. Neural. Inf. Process. Syst. 34, 3965–3977 (2021)

4. Guibas, J., Mardani, M., Li, Z., Tao, A., Anandkumar, A., Catanzaro, B.: Adaptive fourier neural operators: efficient token mixers for transformers. arXiv preprint arXiv:2111.13587 (2021)

5. Harrison, J., Toreini, E., Mehrnezhad, M.: A practical deep learning-based acoustic side channel attack on keyboards. In: 2023 IEEE European Symposium on Security and Privacy Workshops (EuroS &PW), pp. 270–280. IEEE (2023)

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