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Machine Learning
The Netacea Approach | Smarter Bot Management Powered by Machine Learning
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.
What is Machine Learning?
Over the last century, our technology devices have gone from being clunky systems that require tons of human interaction, to modern machines that seem to have a mind of their own. Our phones can do things like autocomplete sentences before we finish typing, suggest purchases based on sites we’ve visited in the past, and even predict our schedules on any given day based on our prior habits. This is all possible due to the growth of artificial intelligence and machine learning.
AI and Machine Learning in Regulated Industries
The hype around artificial intelligence (AI) and machine learning (ML) has exploded, sometimes overshadowing the real uses and innovations happening everyday at organizations across the globe. The reality is that applying AI and ML to data-dependent challenges presents opportunity for better security, faster innovation and overall improved efficiency.
How Machine Data Supports GDPR Compliance
How can you utilize machine data to be prepared for the General Data Protection Regulation of the European Union?
Technology Webinar: ImmuniWeb Application Security Platform
ImmuniWeb® Application Security Testing Platform leverages a machine learning technology for intelligent automation of web vulnerability scanning. Complemented by human intelligence, it detects the most sophisticated web application vulnerabilities and comes with zero false-positives SLA.