Phishing Websites Detection using Machine Learning
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 7
Abstract
Tremendous resources are spent by organizations guarding against and recovering from cybersecurity attacks by online hackers who gain access to sensitive and valuable user data. Many cyber infiltrations are accomplished through phishing attacks where users are tricked into interacting with web pages that appear to be legitimate. In order to successfully fool a human user, these pages are designed to look like legitimate ones. Since humans are so susceptible to being tricked, automated methods of differentiating between phishing websites and their authentic counterparts are needed as an extra line of defense. The aim of this research is to develop these methods of defense utilizing various approaches to categorize websites. Specifically, we have developed a system that uses machine learning techniques to classify websites based on their URL. We used four classifiers: the decision tree, Naïve Bayesian classifier, support vector machine (SVM), and neural network. The classifiers were tested with a data set containing 1,353 real world URLs where each could be categorized as a legitimate site, suspicious site, or phishing site. The results of the experiments show that the classifiers were successful in distinguishing real websites from fake ones over 90% of the time.
Authors and Affiliations
Arun Kulkarni, Leonard L. Brown III
Keywords
Related Articles
- EP ID EP611183
- DOI 10.14569/IJACSA.2019.0100702
- Views 89
- Downloads 0
A New Selection Operator - CSM in Genetic Algorithms for Solving the TSP
Genetic Algorithms (GAs) is a type of local search that mimics biological evolution by taking a population of string, which encodes possible solutions and combines them based on fitness values to produce individuals that...
Advanced Metaheuristics-based Tuning of Effective Design Parameters for Model Predictive Control Approach
This paper presents a systematic tuning approach for Model Predictive Control (MPC) parameters’ using an original LabVIEW-implementation of advanced metaheuristics algorithms. Perturbed Particle Swarm Optimization (pPSO)...
Automatic Scheme for Fused Medical Image Segmentation with Nonsubsampled Contourlet Transform
Medical image segmentation has become an essential technique in clinical and research- oriented applications. Because manual segmentation methods are tedious, and semi-automatic segmentation lacks the flexibility, fully-...
Regression Test-Selection Technique Using Component Model Based Modification: Code to Test Traceability
Regression testing is a safeguarding procedure to validate and verify adapted software, and guarantee that no errors have emerged. However, regression testing is very costly when testers need to re-execute all the test c...
Improving the Recognition of Heart Murmur
Diagnosis of congenital cardiac defects is challenging, with some being diagnosed during pregnancy while others are diagnosed after birth or later on during childhood. Prompt diagnosis allows early intervention and best...