Phish
Our approach first extracts the URL features and then by using the K-Means algorithm, tests whether the page is phishing.
Created on 8th January 2023
•
Phish
Our approach first extracts the URL features and then by using the K-Means algorithm, tests whether the page is phishing.
The problem Phish solves
- Phishing is a very common type of cyber attack that relies on tricking people into giving away sensitive information, such as login credentials or financial information.
- Phishers often use fake websites, emails, or text messages to lure victims into revealing their information. They may pretend to be a legitimate organization, such as a bank or government agency, in order to gain the trust of the victim.
- It is important to be cautious when sharing personal information online and to verify the authenticity of any communication before responding.
- By trying to understand the potential confusion or curiosity of those who might be fooled by a fake link, you may be able to better anticipate and identify situations where they might be more susceptible to falling for a fake link.
- It is important to remember that everyone has different levels of familiarity and experience with the internet, and what may be obvious to one person may not be to another.
Challenges we ran into
- After finding out that the link is fake, we ran it into a machine learning model so that we could get the threshold value saying whether its fake or not.
- We create a website built on Python & Streamlit for users to check if a link is fake or not. We analyze the content of websites and rank the website’s legitimacy
- Linking domain with replit
- Getting to know about DNS
Technologies used
Discussion
Builders also viewed
See more projects on Devfolio
