Performance Analysis of Anti-Phishing Tools and Study of Classification Data Mining Algorithms for a Novel Anti-Phishing System

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Rajendra Gupta 1,* Piyush Kumar Shukla 2

1. BSSS Autonomous College, Barkatullah University, Bhopal - 462024, India

2. University Institute of Technology, Rajiv Gandhi Technical University, Bhopal - 462026, India

* Corresponding author.


Received: 16 Mar. 2015 / Revised: 24 Jun. 2015 / Accepted: 14 Aug. 2015 / Published: 8 Nov. 2015

Index Terms

Phishing, Anti-Phishing, Data Mining Algorithms, Add-on Anti-Phishing Tools


The term Phishing is a kind of spoofing website which is used for stealing sensitive and important information of the web user such as online banking passwords, credit card information and user’s password etc. In the phishing attack, the attacker generates the warning message to the user about the security issues, ask for confidential information through phishing emails, ask to update the user’s account information etc. Several experimental design considerations have been proposed earlier to countermeasure the phishing attack. The earlier systems are not giving more than 90 percentage successful results. In some cases, the system tool gives only 50-60 percentage successful result. In this paper, a novel algorithm is developed to check the performance of the anti-phishing system and compared the received data set with the data set of existing anti-phishing tools. The performance evaluation of novel anti-phishing system is studied with four different classification data mining algorithms which are Class Imbalance Problem (CIP), Rule based Classifier (Sequential Covering Algorithm (SCA)), Nearest Neighbour Classification (NNC), Bayesian Classifier (BC) on the data set of phishing and legitimate websites. The proposed system shows less error rate and better performance as compared to other existing system tools.

Cite This Paper

Rajendra Gupta, Piyush Kumar Shukla, "Performance Analysis of Anti-Phishing Tools and Study of Classification Data Mining Algorithms for a Novel Anti-Phishing System", International Journal of Computer Network and Information Security(IJCNIS), vol.7, no.12, pp. 70-77, 2015. DOI:10.5815/ijcnis.2015.12.08


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