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Detecting Banking Phishing websites using Data Mining Classifiers

EasyChair Preprint no. 2855

4 pagesDate: March 4, 2020

Abstract

Phishing is a malicious, criminal activity executed by obtaining the credentials of system user by unethical means. Phishing has always been a menace in world of internet as it threatens the privacy as well as security of the user. It is executed by multiple means like creating unauthentic webpages, user logins, made-up emails targeting banking sector as well as the ecommerce sector of digital industry. Since the booming of digital market in society the threat of Phishing is eminent. This document explains the existing work and additional work done to counter such conditions and secure the use of internet for the users. Modern day data mining techniques and use of machine learning is used to counter such attacks. We are putting dynamic extension to use for easy access and user protection is enabled for user and is highly optimal.

Keyphrases: Dynamic Extension, machine learning, Phishing, Security

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:2855,
  author = {M. Kanchana and Prabodhan Chavan and Arjun Johari},
  title = {Detecting Banking Phishing websites using Data Mining Classifiers},
  howpublished = {EasyChair Preprint no. 2855},

  year = {EasyChair, 2020}}
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