The Netacea Approach: Machine Learning With Behavioural Analysis
By / 04th Feb 2019
The majority of internet traffic is now made up of bots.
Many bots are malicious, and actively looking for the next opportunity to attack. In fact, bots make 90% of all login attempts. They also pretend to be human, trying to bypass security measures and evade detection by mimicking human behaviour.
Worse, the old defences aren’t enough on their own. Manual analysis, rules-based defences and web application firewalls just can’t keep pace with the ferocity of these attacks. Data breaches are daily headlines and online fraud is growing faster than the security market.
But there is hope
Despite their sophistication, a bot is still a bot.
No matter how it hides, a bot will always behave differently from a genuine user. And to find them, you need a new approach to bot management, one not limited by rules.
Powered by behavioural machine learning, Netacea is agile, intelligent and adaptable. The Netacea layer of protection prevents imitation attacks, stopping automated threats in their tracks. It seamlessly integrates with existing controls and even provides deep, actionable behavioural analysis of all internet traffic. It evaluates web reconnaissance, automated bots and legitimate website visitors, and manage those journeys accordingly in real time.
It’s time to stop the bots.