Algorithm to Develop A Smart System for Detecting Phishing Attack Based on Image Analysis Through Image Quality Parameter and Threshold value

Abstract

This paper represents the design of a system which can be used to detect phishing attack. The proposed system focuses on image analysis through image quality parameter and threshold value. In online money transaction websites hacking or phishing attacks are very usual. Hacking can be controlled & handled through detection and rectification. The integer output value range in any similarity measure is 0 to 1. So after calculating the measure the integer value is compared to the threshold value (1) and then repeats the system until desired result is found. This system can be implemented in Python. The supporting required packages for the implementation are cv2.pyd from OpenCV, Scikit-image and Spipy. This comparison of images is mainly helping us in case of scams during online transaction. This system can validate images of cards, signature, and authenticated logos by the users to avoid any phishing attack by hackers. This system will be used as plug in to net banking sites or other social networking site and user will use it to compare images to find difference real and fake.