Table 1.

State-of-the-Art Learning Based approach.

Paper	Dataset	Potential Approach	Classification Type	Attacks
[8]	BoT-IoT	Learning model (RF, and CNN)	Binary	Botent IoT malware, and IoT network attacks traffic.
[52]	Distilled-Kitsune-2018	Ensemble-based learning	Binary	OS scan, ARP, SSDP, SSL, and Maria attacks.
[53]	KDD cup’99 and NSL-KDD	Naïve Base, KNN, RF, and DT algorithms.	Binary	DoS, Sybil and Spoofing, Man-in-the-middle, Hole ataacks.
[54]	NSL-KDD	Ensemble-based learning	Multi-Class	DDoS Attacks, and IoT network attacks traffic.
[55]	Network Traffic	Ensemble-based learning	Binary/Multi-Class	Data theft, DoS, and spam
[56]	NSL-KDD	Ensemble-based learning	Binary	DDoS Attacks, and IoT network attacks traffic.
[57]	IoT Network Traffic	K-means	Binary	Ping flood Attacks