Detecting Phishing Websites Using Machine Learning
Detecting Phishing Websites – BACKGROUND OF THE STUDY
For any computer and internet users, it is important we keep information safe , secure and reduce to the barest minimum the instance of fraud that may arise in the course of visiting various websites.
Phishing is one problem that has been identified since the beginning of the internet age, and is one of the the more difficult to prevent and curtail.
Phishing is defined as a a cyber crime in which a target or targets are contacted by email, telephone or text message by someone posing as a legitimate institution to lure individuals into providing sensitive data such as personally identifiable information, banking and credit card details, and passwords.
The information is then used to access important accounts and can result in identity theft and financial loss.
The first phishing lawsuit was filed in 2004 against a Californian teenager who created the imitation of the website “America Online”. With this fake website, he was able to gain sensitive information from users and access the credit card details to withdraw money from their accounts.
Other than email and website phishing, there’s also ‘vishing’ (voice phishing), ‘smishing’ (SMS Phishing) and several other phishing techniques cybercriminals are constantly coming up with. The study wants to focus on the various ways phishing can be done and possible solutions to them in form of a machine learning based software.