Detecting Phishing Websites using Machine Learning Techniques

The project “Detecting Phishing Websites using Machine Learning Techniques” aims to develop a method that can accurately identify and block malicious websites. Machine Learning algorithms will be used to analyze various website features, such as URL, page content, rank and other indicators to determine if it is a phishing site or not. By identifying and blocking these websites before they can cause harm, the system will save time and resources while also preventing the loss of sensitive information. With the increasing threat of cyber attacks, this project is essential for ensuring enhanced safety of browsing. Leveraging the power of Machine Learning, the research has the potential to make a significant impact in the fight against phishing.

The expected outcome of this project is a report describing a method that can later be used to develop reliable and efficient tool to help individuals, organizations and state agencies protect themselves from falling victim to phishing attacks.

Faculty Supervisor:

Anwar Hasan

Student:

Partner:

Taras Shevchenko National University of Kyiv

Discipline:

Computer science

Sector:

Information and Communications Technology; Artificial Intelligence; Technology

University:

University of Waterloo

Program: