Trend Micro integrates machine learning in network defence
Trend Micro TippingPoint NGIPS to include machine learning to detect threats
Trend Micro is including machine learning capabilities in its latest network security solutions, to improve detection of malicious behaviour and traffic on customer networks.
The patent-pending machine learning technology is built in to Trend Micro TippingPoint next-generation intrusion prevention system (NGIPS) solutions, to help detect and block attacks in real time.
Trend Micro TippingPoint NGIPS applies machine learning statistical models to feature vectors extracted from network data on the wire to make a real-time decision on whether network traffic is malicious or benign. This evolution helps to better detect advanced malware behaviour and communications invisible to standard defences.
TippingPoint NGIPS also applies machine learning techniques to detect and block known and unknown malware families that use domain generation algorithms (DGAs) to generate domain names for infected hosts attempting to contact their command and control servers.
"Protecting an enterprise network is a vital part of a connected threat defence that should also include servers and endpoints," said Steve Quane, executive vice president and chief product officer for Trend Micro TippingPoint. "As businesses grow, the need is greater to have a solution that can provide visibility and control within any customer environment while sharing threat intelligence across security layers."
TippingPoint NGIPS is part of the Trend Micro Network Defense solution which, in combination with advanced threat protection, is optimized to prevent targeted attacks, advanced threats and malware from embedding or spreading within a data centre or network. Network Defense is powered by XGen security, a blend of cross-generational threat defence techniques specifically designed for leading customer platforms and applications and fuelled by market-leading threat intelligence.
"Our enterprise clients inquire regularly about the need to protect their networks from existing and emerging threats," said Andrew Braunberg, managing director of research for NSS Labs. "Enterprises are continuing to deploy NGIPS devices, particularly to protect high value assets, such as data centres. Advanced analytics, such as machine learning, and fully integrated global threat intelligence feeds are particularly important features for today's leading NGIPS products."