Malware Traffic Classification Based on GAN and BP Neural Networks

Author:

Duan Yun,Wang Laifu,Liu Dongxin,Deng Boren,Tian Yunfan

Publisher

Springer Nature Singapore

Reference33 articles.

1. Liu, M., Hong, Z., Liu, Q., Xing, X., Dai, Y.: A backdoor embedding method for backdoor detection in deep neural networks. In: Wang, G., Choo, K.K.R., Ko, R.K.L., Xu, Y., Crispo, B. (eds.) Ubiquitous Security. UbiSec 2021. Communications in Computer and Information Science, vol. 1557, pp. 1–12. Springer, Singapore (2022). https://doi.org/10.1007/978-981-19-0468-4_1

2. Lin, J., Wei, Y., Li, W., Long, J.: Intrusion detection system based on deep neural network and incremental learning for in-vehicle CAN networks. In: Wang, G., Choo, K.K.R., Ko, R.K.L., Xu, Y., Crispo, B. (eds.) Ubiquitous Security. UbiSec 2021. Communications in Computer and Information Science, vol. 1557, pp. 255–267. Springer, Singapore. https://doi.org/10.1007/978-981-19-0468-4_19

3. Tang, Y., Zhang, D., Liang, W., Li, KC., Sukhija, N.: Active malicious accounts detection with multimodal fusion machine learning algorithm. In: Wang, G., Choo, K.K.R., Ko, R.K.L., Xu, Y., Crispo, B. (eds.) Ubiquitous Security. UbiSec 2021. Communications in Computer and Information Science, vol. 1557, pp. 38–52. Springer, Singapore. https://doi.org/10.1007/978-981-19-0468-4_4

4. Keipour, H., Hazra, S., Finne, N., Voigt, T.: Generalizing supervised learning for intrusion detection in IoT mesh networks. In: Wang, G., Choo, K.K.R., Ko, R.K.L., Xu, Y., Crispo, B. (eds.) Ubiquitous Security. UbiSec 2021. Communications in Computer and Information Science, vol. 1557, pp. 214–228. Springer, Singapore (2022). https://doi.org/10.1007/978-981-19-0468-4_16

5. Li, W., Cai, J., Wang, Z., Cheng, S.: A robust malware detection approach for android system based on ensemble learning. In: Wang, G., Choo, K.K.R., Ko, R.K.L., Xu, Y., Crispo, B. (eds.) Ubiquitous Security. UbiSec 2021. Communications in Computer and Information Science, vol. 1557, pp. 309–321. Springer, Singapore (2022). https://doi.org/10.1007/978-981-19-0468-4_23

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