TY  - JOUR
AU  - Syurahbil, 
AU  - Ahmad, Noraziah 
AU  - Zolkipli, M. Fadly 
AU  - Abdalla, Ahmed N. 
PY  - 2009
TI  - Intrusion Preventing System using Intrusion Detection System Decision Tree Data Mining 
JF  - American Journal of Engineering and Applied Sciences
VL  - 2
IS  - 4
DO  - 10.3844/ajeassp.2009.721.725
UR  - https://thescipub.com/abstract/ajeassp.2009.721.725
AB  - Problem statement: To distinguish the activities of the network traffic that the intrusion and normal is very difficult and to need much time consuming. An analyst must review all the data that large and wide to find the sequence of intrusion on the network connection. Therefore, it needs a way that can detect network intrusion to reflect the current network traffics. Approach: In this study, a novel method to find intrusion characteristic for IDS using decision tree machine learning of data mining technique was proposed. Method used to generate of rules is classification by ID3 algorithm of decision tree. Results: These rules can determine of intrusion characteristics then to implement in the firewall policy rules as prevention. Conclusion: Combination of IDS and firewall so-called the IPS, so that besides detecting the existence of intrusion also can execute by doing deny of intrusion as prevention.