Table 1.

Summary of Related Works.

Author and Citation	Contribution	Limitation
Pajila and Julie [47]	Reviewed the potential of using machine learning techniques as one DDoS attacks detection mechanism in SDN networks	Few works of literature were included in their work
Shinan et al. [48]	Surveyed literature that focuses on detecting botnets using machine learning techniques in traditional networks	Did not focus on SDN-enabled IoT networks botnet attacks
Snehi et al. [51]	A detailed survey and discussion on improving the performance of Software-defined cyber-physical systems through architectural redesigning have been presented.	The contribution of machine learning techniques in improving the cyber-physical security of SDN-enable IoT networks did not present.
Cui et al. [52]	Comprehensive review on DDOS identification. Classification of DDOS detection mechanisms is proposed, that makes it	In this survey botnet detection using a machine learning approach on SDN-based IoT devices is not conducted.
Aversano et al. [53]	Summarizes recently conducted studies in the area of deep learning applications on IoT Security. Identifies the datasets used by different deep learning architectures for IoT security.	The review did not specify which type of security threat and machine learning-based solutions for botnets in an SDN-enabled IoT.
Ismael et al. [54]	Comprehensive surveys of DDoS detection and mitigation techniques are made	Recommendation of the selected architecture or technique is not properly addressed. The survey did not include SDN-IoT botnets