TY  - JOUR
TI  - Finding Fraud Websites by Using Data Mining Techniques
AU  -  Maheswari G
AU  -  Madhura P
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2018/03/31
PY  - 2018
DO  - https://doi.org/10.32628/IJSRCSEIT
UR  - https://ijsrcseit.com/CSEIT1833582
VL  - 3
IS  - 4
SP  - 1195	
EP  - 1198
AB  - Globally the internet is been accessed by huge amount people inside their restricted domains. once the client and server exchange messages among one another, there's an activity that may be observed in log files. Log files provides a elaborated description of the activities that occur in an exceedingly network that shows the IP address, login and logout durations, the user’s behavior etc. There are many varieties of attacks occurring from the net. Our focus of analysis is on Denial of Service (DOS) attacks with the help of pattern recognition techniques in data processing. Through that the Denial of Service attack is known. Denial of service is a terribly dangerous attack that jeopardizes the IT resources of a corporation by overloading with imitation messages or multiple requests from unauthorized users. But we cannot detect the fake website in this criteria. In order to detect and predict e-banking phishing website, we proposed an intelligent, flexible and effective system that is based on using classification Data mining algorithm. We implemented classification algorithm and techniques to extract the phishing data sets criteria to classify their legitimacy.