Fortinet Adds Machine Learning Algorithms to WAF - Security Boulevard

Fortinet today at the Gartner Security & Risk Management Summit 2018 announced it has infused machine learning algorithms and user-behavioral analytics in its web application firewall to identify nearly 100 percent of all cyberthreats. John Maddison, senior vice president of products and solutions for Fortinet, said version 6.0 of the company's FortiWeb Web Application Firewall (WAF) software employs machine learning algorithms to identify both known and unknown threats. That latter capability is enabled by applying algorithms against the user behavior data being collected to identify anomalies indicative of a new, unknown threat being introduced into the IT environment. Historically, WAFs have relied on application learning (AL) to identify anomalies and known threats. But Maddison said that approach generates too many security alerts, which ultimately leads to a state of alert fatigue that makes it easy for cybersecurity professionals to miss or ignore critical information.