Abstract
Abstract: One of the greatest hazards to websites and web portals of private and public entities has been website attacks. In today's digital world, web applications play a significant role in daily life, making their security a difficult challenge. Through the URL links that are delivered to the victims, the attackers hope to obtain private information about the users. We are attempting to plug the gaps left by conventional means to combat the assaults, but these conventional measures are ineffective since attackers are getting better at targeting online apps. Currently, people are looking for software that can consistently and reliably identify web application attacks. Using machine learning, this approach seeks to protect online applications from flaws and many sorts of attacks.
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