Table 2 Comparisons between researches that used SVM as basic classifier

Unsupervised anomaly detection system [6]

Tune and optimize automatically the values of parameters without pre-defining them

From Kyoto University honeypot

–

–

Multiclass SVM [7]

Attributes are optimized using k-fold cross validation. This technique can be used to decrease the rate of False-Negatives in the IDS

Self

–

–

OC-SVM One-Class SVM [8]

Multistage OC-SVM and feature extraction represents a method to detect unknown attacks. Method is poor in second stage classifier to detection rate of unknown attacks

From Kyoto

80.00

20.94

IG-ABC-SVM Information Gain-Artificial Bee Colony [9]

A combining IG feature selection and SVM classifier in IDS model is proposed. Experiments using just two swarm intelligence algorithms

NSL-KDD

98.53

0.03

SbSVM [10]

Autonomous labeling algorithm of normal traffic (when the class distribution is not imbalanced). Not evaluated for real-time case

DARPA

99

5.5

RS-ISVM-reserved set-incremental SVM [11]

An incremental SVM training algorithms is used, hybrid with modifying kernel function U-RBF Foreseeing attacks, specifically for attacks of U2R and R2L may not tolerate but oscillation problem solved

KDD Cup 1999

89.17

4.9

SVM-GA [12]

Hybrid model by combining (GA and SVM)

KDD CUP 1999

98.33

0.50

Genetic principal component [13]

Subset selection using GA and PCA

KDD cup 1999

99.96

0.49

SVM and NN [14]

Hybrid process. Most significant performance as far as training time but time consuming and hard task to trigger

DARPA

99.87

–

N-KPCA-GA-SVM kernel PCA genetic algorithm-SVM [15]

Hybrid of KPCA, SVM and GA algorithms. Faster convergence speed. Performs higher predictive accuracy and better generalization. But have complex structure and have latency for real-time application

KDD CUP99

96.37

0.95

CSV-ISVM Candidate Support Vector-Incremental SVM [16]

Improved learning algorithm to better recognize rate and false alarm rate than usual classification

KDD Cup 1999

90.14

2.31