Survey on Botnet Detection Techniques: Classification, Methods, and Evaluation

Table 1

Comparison with other surveys.

Survey	Published time	Detection targeted	Background	Detection methods/techniques	Evaluation
[9]	2020	IoT	(i) Architecture	Neural networks data mining graph theory	(i) Not included
			(ii) Life cycle
[10]	2020	IoT	(i) Not included	Machine learning	(i) Measurement
				Deep learning
				Statistical analysis
				Propagation model
[11]	2019	DNS	(i) Not included	Machine learning statistical analysis	(i) Not included
				Whitelist/blacklist
[12]	2018	Universal	(i) Architecture	Signature-based	(i) Not included
			(ii) Life cycle	Mining-based
[13]	2015	DNS	Life cycle	Graph theory	(i) Not included
				Statistical analysis
				Clustering
				Decision tree
				Neural network
[14]	2017	DNS	C&C channel	Characteristics analysis statistical analysis	(i) Not included
[15]	2016	Universal	(i) Architecture	Honeypot analysis statistical analysis	(i) Not included
			(ii) Life cycle
Our method	—	Universal	(i)Architecture	Deep learning, complex network, swarm intelligence, MTD, SDN, blockchain, etc.	Common bot detection evaluation system
			(ii)Life cycle
			(iii)C&C channel