Detection of Malware in the Network Using Machine Learning Techniques

The increased use of the internet has presented the most significant challenge to the digital world's security. Malicious URLs are the most common way for people to engage in phishing schemes and spread viruses like trojans and worms. Various dangerous URLs attempt to obtain user information by distributing different harmful malware. End-users can be susceptible if a genuine user is unable to recognize and remove fraudulent URLs. Attackers can potentially acquire unauthorized access to user data by using malicious URLs. As a result, identifying countermeasures to halt such operations using new and advanced technology is a critical step. One of its most effective methods has been thought to be based on ML approaches for correctly identifying a URL as malicious or benign. The project's main goal is to deploy the system in a way that is both efficient and accuracy.