1. Chiba, Z., Abghour, N., Moussaid, K., El Omri, A., Rida, M.: Intelligent and improved self-adaptive anomaly based intrusion detection system for networks. Int. J. Commun. Netw. Inf. Sec. 11(2), 312–330 (2019)
2. Papamartzivanos, D., Mármol, F.G., Kambourakis, G.: Introducing deep learning self-adaptive misuse network intrusion detection systems. IEEE Access 7, 13546–13560 (2019)
3. Shukla, A.K.: Detection of anomaly intrusion utilizing self-adaptive grasshopper optimization algorithm. Neural Comput. Appl. 33(13), 7541–7561 (2021)
4. Pawar, M.V., Jagadeesan, A.: Detection of blackhole and wormhole attacks in WSN enabled by optimal feature selection using self-adaptive multi-verse optimiser with deep learning. Int. J. Commun. Netw. Distrib. Syst. 26(4), 409–445 (2021)
5. Zhang, Y., Li, P., Wang, X.: Intrusion detection for IoT based on improved genetic algorithm and deep belief network. IEEE Access 7, 31711–31722 (2019)