Phishing Websites Detection using Python

Phishing websites is one of the security problems on Internet that target the human vulnerabilities rather than software vulnerabilities. It can be described as it is the process of attracting online users for obtain their sensitive information such as usernames and passwords. Types of web pages are different in terms of their features. Phishing is a form of identity theft that occurs when a malicious Web site impersonates a legitimate one in order to acquire sensitive information such as passwords, account details, or credit carPhishing websites is a problem on internet that target the people amenabilities rather than software vulnerabilities. It can be described as it is the process of collecting sensitive information such as usernames and passwords. Types of web pages are different in terms of their features. Phishing occurs when a malicious site acts as a legitimate for obtaining sensitive information such as passwords, account information, or credit card numbers. Phishing attacks can be prevented by detecting websites and notifying users to detect phishing websites. Machine learning algorithms have been one of the most effective techniques for detecting phishing websites. Nowadays, information and communication tools are used in a manner that is very dense with information. For this purpose, various solution methods are developed for various problem. Machine Learning (ML) methods be used in application development for in security purpose. Prediction and decision support system and great benefits can be provided to the person who is responsible for information security. Today, it has become an increasingly popular subject in developing intelligent application. Hence, we use a web page features set to avoid phishing attacks. We proposed a model based on machine learning techniques to detect phishing web pages. We have suggested some rules to have efficient features. The model has 13 inputs and 1 output. The average classification accuracy was measured as 75%.d numbers. Phishing attacks can be prevented by detecting the websites and creating awareness to users to identify the phishing websites. Machine learning algorithms have been one of the powerful techniques in detecting phishing websites. Nowadays, information and communication tools are used in a manner that is very dense with information. For this purpose, various solution methods for various problem types have been developed. Machine Learning(ML) methods, can also be used in application development for information security. Optimization, classification, prediction and decision support system and great benefits can be provided to the person who is responsible for information security. Today, it has become an increasingly popular subject in developing intelligent application. Hence, we use a web page features set to avoid phishing attacks. We proposed a model based on machine learning techniques to detect phishing web pages. We have suggested some rules to have efficient features. The model has 13 inputs and 1 output. The average classification accuracy was measured as 75%.