Article

Classification Technique

Class name

Results

AA

TT (sec)

Test time (sec)

TP

TN

FP

FN

Error rate

Precision

Recall

DR

FAR

10: Application of Data mining to Network Intrusion detection: Classifier selection model

Bayes Net

Dos

90.62%

628

.

94.60%

.

0.20%

.

.

.

.

.

.

Probe

88.80%

.

0.12%

.

.

.

.

.

.

U2R

30.30%

.

0.30%

.

.

.

.

.

.

R2L

5.20%

.

0.60%

.

.

.

.

.

.

Naïves Bayes

Dos

78.32%

557

.

79.20%

.

1.70%

.

.

.

.

.

.

Probe

94.80%

.

13.30%

.

.

.

.

.

.

U2R

12.20%

.

0.90%

.

.

.

.

.

.

R2L

0.10%

.

0.30%

.

.

.

.

.

.

J48

Dos

92.06%

1585

.

96.80%

.

1.00%

.

.

.

.

.

.

Probe

75.20%

.

0.20%

.

.

.

.

.

.

U2R

12.20%

.

0.10%

.

.

.

.

.

.

R2L

0.10%

.

0.50%

.

.

.

.

.

.

NB Tree

Dos

92.28%

295.88

.

97.40%

.

1.20%

.

.

.

.

.

.

Probe

73.30%

.

1.10%

.

.

.

.

.

.

U2R

1.20%

.

0.10%

.

.

.

.

.

.

R2L

0.10%

.

0.50%

.

.

.

.

.

.

Decision Table

Dos

91.66%

6624

.

97%

.

10.70%

.

.

.

.

.

.

Probe

57.60%

.

40%

.

.

.

.

.

.

U2R

32.80%

.

0.30%

.

.

.

.

.

.

R2L

0.30%

.

0.10%

.

.

.

.

.

.

Jrip

Dos

0.923

207.47

.

97.40%

.

0.30%

.

.

.

.

.

.

Probe

83.80%

.

0.10%

.

.

.

.

.

.

U2R

12.80%

.

0.10%

.

.

.

.

.

.

R2L

0.10%

.

0.40%

.

.

.

.

.

.

One R

Dos

0.8931

375

.

94.20%

.

6.80%

.

.

.

.

.

.

Probe

12.90%

.

0.10%

.

.

.

.

.

.

U2R

10.70%

.

2.00%

.

.

.

.

.

.

R2L

10.70%

.

0.10%

.

.

.

.

.

.

MLP

Dos

0.9203

350.15

.

96.90%

.

1.47%

.

.

.

.

.

.

Probe

74.30%

.

0.10%

.

.

.

.

.

.

U2R

20.10%

.

0.10%

.

.

.

.

.

.

R2L

0.30%

.

0.50%

.

.

.

.

.

.