A Methodical Overview on Detection, Identification and Proactive Prevention of Phishing Websites
Manisha Bhagwat, Pooja Patil, T. S. Vishawanath
Abstract
Detecting and finding some phishing websites in real-time for a day now is really a dynamic and nuanced topic involving several variables and requirements. Fuzzy logic strategies may be an important method in detecting and testing phishing websites due to the ambiguities involved in the detection. Instead of exact principles, Fuzzy logic provides a more intuitive way of dealing with quality variables. An approach to fuzziness resolution and an open and intelligent phishing website detection model will be proposed in the Phishing website assessment. This approach is based on smooth logic and machine learning algorithms that define various factors on the phishing website. A total of 30 characteristics or features and phishing website attributes can be used for phishing detection with high accuracy. A real-time phishing dataset is used which is downloaded from the UCI machine learning repository.