ConvNet Based Malicious URL Identification for Safer Use
Vinod Sapkal, Praveen Kumar Gupta · Revue d intelligence artificielle · 2023
A malicious URL or website is a type of threat that can affect the users' cybersecurity.It can host unsolicited content and lure users into clicking on links and downloading malware.It can also lead to the theft of private information and monetary losses.People must take the necessary steps to prevent these types of threats from happening promptly.Unfortunately, denylists are not capable of identifying new malicious content.Instead, they are mainly used to identify existing threats.Due to the increasing number of studies being conducted on the use of machine learning techniques, the general capabilities of these tools have been improved.The rise of the internet has made it an essential component of our lives.It allows us to exchange information and knowledge in a timelier manner.Unfortunately, identity fraud and identity theft are two of the most common forms of cybercrime.In both cases, the attackers' goal is to collect the users' personal data so they can commit fraud or deceit for financial gain.Phishing, drive-by exploits, and spam are some types of content commonly featured in malicious URLs.They are also designed to trick users into clicking on links and downloading malware.The vast majority of these scams are carried out through email, and they result in losses of billions of dollars.Systems that are capable of quickly identifying and preventing these types of crimes need to be developed, as well as have the ability to spot new malicious content.Blacklist methods have traditionally been used to detect these types of crimes.On the other hand, blacklists cannot identify newly produced harmful content.Due to the increasing number of studies being conducted on machine learning techniques to improve the detection of harmful web pages, the focus on this field has increased.This article presents an algorithm that can analyze and predict the likelihood of a link being good or bad.It is compared with other standard methods to analyze the performance of this method.