An Effective Conversation-Based Botnet Detection Method

Algorithm 2

Feature selection algorithm.

Input: train_data a labeled training set, test_data a labeled testing set

Output: PF a list of promising features

(1) an error range, the botnet traffic detection rate,

the current botnet traffic detection rate

(2) initialization ,

(3) = Randonforest (all features)

(4) while    do

(5) 

(6) calculate RF scores of importance

(7) rank the RF scores

(8) delete the feature with the smallest importance from train_data and test_data

(9) = randomforest (remaining_features)

(10) end while