This work is licensed under the Creative Commons Attribution 4.0 International License.
Aoudni, Y., Donald, C., Farouk, A., Sahay, K. B., Babu, D. V., & Tripathi, V., et al. (2022). Cloud security based attack detection using transductive learning integrated with hidden markov model. Pattern recognition letters (May), 157.Search in Google Scholar
He, J., Yang, J., Ren, K., Zhang, W., & Li, G. (2019). Network security threat detection under big data by using machine learning. International Journal of Network Security, 21(5), 768–773.Search in Google Scholar
ZHOU, Aiping, LIU, Lijun, ZHU, & Huisheng, et al. (2018). Parallel sketch based super node detection with traceability. Chinese Journal of Electronics.Search in Google Scholar
Jiang, W., Pan, S., Lu, C., Zhao, Z., Lin, S., & Xiong, M., et al. (2021). Label entropy-based cooperative particle swarm optimization algorithm for dynamic overlapping community detection in complex networks. International Journal of Intelligent Systems.Search in Google Scholar
Hadid, R., Karaata, M. H., & Villain, V. (2017). A stabilizing algorithm for finding two node-disjoint paths in arbitrary networks. International Journal of Foundations of Computer Science, 28(04), 411–435.Search in Google Scholar
Shah, V. M., & Agarwal, A. K. (2017). Reliable alert fusion of multiple intrusion detection systems. International Journal of Network Security, 19(2), 182–192.Search in Google Scholar
Cintas, C., Speakman, S., Tadesse, G. A., Akinwande, V., Mcfowland, E., & Weldemariam, K. (2022). Pattern detection in the activation space for identifying synthesized content. Pattern Recognition Letters, 153.Search in Google Scholar
Boujnouni, M. E., & Jedra, M. (2018). New intrusion detection system based on support vector domain description with information gain metric. International Journal of Network Security, 20(1), 25–34.Search in Google Scholar
Lu, R., Jiao, P., Wang, Y., Wu, H., & Chen, X. (2021). Layer information similarity concerned network embedding. Complexity.Search in Google Scholar
Feng, P., Ma, J., Li, T., Ma, X., & Lu, D. (2021). Android malware detection via graph representation learning. Mobile Information Systems, 2021(6), 1–14.Search in Google Scholar
Bou-Harb, E., Debbabi, M., & Assi, C. (2017). Big data behavioral analytics meet graph theory: on effective botnet takedowns. IEEE Network, 31(1), 18–26.Search in Google Scholar
Amrita, & Ravulakollu, K. K. (2018). A hybrid intrusion detection system: integrating hybrid feature selection approach with heterogeneous ensemble of intelligent classifiers. International Journal of Network Security, 20(1), 40–53.Search in Google Scholar
Ansari, M. H., & Vakili, V. T. (2017). Detection of clone node attack in mobile wireless sensor network with optimised cost function. International Journal of Sensor Networks, 24(3), 149.Search in Google Scholar
Youquan, W., Jie, C., & Haicheng, T. (2023). Graph convolutional network with multi-similarity attribute matrices fusion for node classification. Neural computing & applications.Search in Google Scholar
Kshirsagar, V. H., Kanthe, A. M., & Simunic, D. (2017). Trust based detection and elimination of packet drop attack in the mobile ad-hoc networks. Wireless Personal Communications.Search in Google Scholar
Dong, R. H., Wu, D. F., Zhang, Q. Y., & Zhang, T. (2018). Traffic characteristic map-based intrusion detection model for industrial internet. International Journal of Network Security, 20.Search in Google Scholar
Luo, S., Lai, Y., & Liu, J. (2023). Selective forwarding attack detection and network recovery mechanism based on cloud-edge cooperation in software-defined wireless sensor network. Computers & Security, 126, 103083-.Search in Google Scholar
Gilberto, F., Rodrigues, J. J. P. C., Fernando, C. L., Al-Muhtadi, J. F., & Lemes, P. M. (2018). A comprehensive survey on network anomaly detection. Telecommunication Systems.Search in Google Scholar
Zheng, G., Gong, B., & Zhang, Y. (2021). Dynamic network security mechanism based on trust management in wireless sensor networks. Wireless Communications and Mobile Computing.Search in Google Scholar
Steno, P., Alsadoon, A., Prasad, P. W. C., Al-Dala’In, T., & Alsadoon, O. H. (2021). A novel enhanced region proposal network and modified loss function: threat object detection in secure screening using deep learning. Journal of supercomputing (4), 77.Search in Google Scholar
Michael P. Atkinson & Moshe Kress. (2023). Resource allocation in two‐layered cyber‐defense. Naval Research Logistics (NRL)(6), 574–583.Search in Google Scholar
US Army Research Laboratory, USA,US Army Research Laboratory, USA & US Army Research Laboratory, USA. (2020). The game-theoretic model and experimental investigation of cyber wargaming. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology (1), 21–38.Search in Google Scholar
Jing Jing. (2022). Applications of Game Theory and Advanced Machine Learning Methods for Adaptive Cyberdefense Strategies in the Digital Music Industry. Computational Intelligence and Neuroscience 2266171–2266171.Search in Google Scholar
Linan Huang & Quanyan Zhu. (2019). Adaptive Strategic Cyber Defense for Advanced Persistent Threats in Critical Infrastructure Networks. ACM SIGMETRICS Performance Evaluation Review (2), 52–56.Search in Google Scholar