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Papadogiannaki, E., & Ioannidis, S. (2021). A survey on encrypted network traffic analysis applications, techniques, and countermeasures. ACM Computing Surveys (CSUR).Search in Google Scholar
Pathak, Parth, H., Chuah, Chen-Nee, & Mohapatra, et al. (2017). Privacy-aware contextual localization using network traffic analysis. Computer Networks.Search in Google Scholar
Yang, L. S. (2018). Botcapturer: detecting botnets based on two-layered analysis with graph anomaly detection and network traffic clustering. International Journal of Performability Engineering, 14(5).Search in Google Scholar
Duan, L., Zhou, J., Wu, Y., & Xu, W. (2022). A novel and highly efficient botnet detection algorithm based on network traffic analysis of smart systems:. International Journal of Distributed Sensor Networks, 18(3), 182459-182476.Search in Google Scholar
Zhu, Y., & Du, Z. (2021). Research on the key technologies of network security-oriented situation prediction. Scientific Programming.Search in Google Scholar
Krupski, J., Graniszewski, W., & Iwanowski, M. (2021). Data transformation schemes for cnn-based network traffic analysis: a survey. Electronics(16).Search in Google Scholar
Kim, J., Sim, A., Tierney, B., Suh, S., & Kim, I. (2018). Multivariate network traffic analysis using clustered patterns. Computing, 101(4), 1-23.Search in Google Scholar
Guan, W., Zhang, H., & Leung, V. C. M. (2020). Analysis of traffic performance on network slicing using complex network theory. IEEE Transactions on Vehicular Technology, 69(12), 15188-15199.Search in Google Scholar
Li, D., Cui, J., & Fan, Q. (2017). Similarity analysis and simulation experiment of network video traffic. Revista de la Facultad de Ingenieria, 32(5), 372-379.Search in Google Scholar
Doan, E. (2020). Analysis of the relationship between lstm network traffic flow prediction performance and statistical characteristics of standard and nonstandard data. Journal of Forecasting.Search in Google Scholar
Guang, K., Shuo, W., & Guangming, T. (2019). Research on key technologies of network security situational awareness for attack tracking prediction. Chinese Journal of Electronics, 28(01), 166-175.Search in Google Scholar
Zhou, W. (2022). Big data-driven hierarchical local area network security risk event prediction algorithm. Scientific Programming.Search in Google Scholar
Liu, D. (2020). Prediction of network security based on ds evidence theory. ETRI Journal.Search in Google Scholar
Xing, J., & Zhang, Z. (2021). Prediction model of network security situation based on genetic algorithm and support vector machine. Journal of Intelligent and Fuzzy Systems(3), 1-9.Search in Google Scholar
Ma, X., Chen, X., & Zhang, X. (2019). Non-interactive privacy-preserving neural network prediction. Information Sciences, 481, 507-519.Search in Google Scholar
Sun, L., & Gao, D. (2022). Security attitude prediction model of secret-related computer information system based on distributed parallel computing programming. Mathematical Problems in Engineering, 2022.Search in Google Scholar
Yu, H., Yang, X., & Wang, L. (2020). Network security situation prediction based on combining associated entropy and deep recurrent neural network. Transactions on Emerging Telecommunications Technologies.Search in Google Scholar
Assadhan, B., Zeb, K., Al-Muhtadi, J., & Alshebeili, S. (2017). Anomaly detection based on lrd behavior analysis of decomposed control and data planes network traffic using soss and farima models. IEEE Access, 13501-13519.Search in Google Scholar
Shahraki, A., Abbasi, M., Taherkordi, A., & Jurcut, A. D. (2022). A comparative study on online machine learning techniques for network traffic streams analysis. Computer networks(Apr.22), 207.Search in Google Scholar
Manivannan, R., & Chinnadurai, M. (2020). Analysis of energy efficient and network traffic delay in wireless networks using channel aware routing. Transactions on Emerging Telecommunications Technologies(3).Search in Google Scholar
Lyamin, N., Kleyko, D., Delooz, Q., & Vinel, A. (2018). Ai-based malicious network traffic detection in vanets. IEEE Network, 32(6), 15-21.Search in Google Scholar
Sapio, A., Baldi, M., Risso, F., Anand, N., & Nucci, A. (2017). Packet capture and analysis on medina, a massively distributed network data caching platform. Parallel Processing Letters.Search in Google Scholar
Reece, T., Sathyanarayana, S., Robinson, W. H., & Beyah, R. A. (2017). On the outside looking in: towards detecting counterfeit devices using network traffic analysis. IEEE Transactions on Multi-Scale Computing Systems, PP(1), 50-61.Search in Google Scholar