Detection of Phishing Attacks using Visual Similarity Model

Abstract

Phishing is a huge problem in the online world, costing businesses and individuals money. Fraudulently replicating an existing online page to trick users into providing their personal, financial, or other transactional information is known as phishing. This type of assault is carried out by creating a copy of the original web page. In this point, hackers are highly proficient at exploiting their expertise and breaking into the systems of others in order to steal their data. Phishing is a type of cybercrime that involves posing as a legitimate business in order to get access to a victim's personal information, such as bank account numbers, credit card numbers, and other sensitive information. Phishing is primarily an internet robbery technique. In order to fool consumers into thinking they are on a legitimate website, a Phishing site looks exactly like the equivalent legal site. It is possible to utilise visual similarity oriented phishing detection approaches to make decisions based on factors such as text content, HTML elements and Cascading Style Sheets (CSS). By comparing the suspected website with its corresponding legal counterpart, this method determines whether or not it is a case of Phishing when there is a high degree of resemblance in features. Deceptive phishing & malware-based phishing are two distinct types of phishing. Various anti-phishing strategies have been devised to keep users secure from attackers. A visual similarity-based method to combat phishing attempts is presented in this work in order to provide readers a better knowledge of the problem, currently selected space, and potential future research directions.