Fortinet Becomes First WAF Vendor Using Machine Learning

- June 5th, 2018

According to its announcement on Tuesday (June 5) Fortinet has officially become the first major vendor to use machine learning for behavioral-based threat detection.

Fortinet (NASDAQ:FTNT), a company focused on cybersecurity solutions has become the first major Web Application Firewall (WAF) vendor to use machine learning for behavioral-based threat detection in web applications.

On Tuesday (June 5) the company announced the launch of the latest version of FortiWeb Web Application Firewall software.

According to the press release, the new innovations to FortiWeb provide a “dramatic increase in detecting web applications threats with nearly 100 percent accuracy.”

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John Maddison, senior vice president at Fortinet, said that 48 percent of data breaches has been caused by hacking web application vulnerabilities and that cybercriminals are targeting public and internal web applications.

“Current technologies such as intrusion prevention systems and existing web application security solutions only provide basic protection against these threats,” Maddison said in the release.

The announcement happened at the ongoing Gartner Security and Risk Management Summit 2018 where Gartner highlighted the importance of machine learning in this space.

According to Gartner, machine learning will be a normal part of security practice by 2025 and will offset some skills and staffing shortfalls.  The agency claims that machine learning is “better at addressing narrow and well-defined problem sets, such as classifying executable files.”

“We cannot escape the immutable fact that humans and machines complement each other,” Peter Firstbrook, research vice president at Gartner said at the summit. “Together they can outperform either alone.”

Further, Gartner said that security and risk management (SRM) leaders should focus on how AI makes its product superior in terms of efficacy and administrative requirements.

Fortinet on its part said that traditionally, WAFs have relied on application learning (AL) for anomaly and threat detection but in today’s dynamic and threat landscape, AL has proven to have limitations.

According to Fortinet, AL uses one-layer approach to detect anomalies based on simply matching inputs to what it has observed which would mean that it treats every variation on system as a threat. This limitation affected the security teams who were already bogged down due to understaffing and other constraints required to spend a significant amount of time in dealing with threats.

The company said that its new software with machine learning compensates for every limitations of AL with its two layer approach, AI based machine learning and statistical probabilities to detect anomalies and threats separately.

Following the announcement on Tuesday, Fortinet closed the trading at US$63.20 and was up 1.17 percent over the one day trading period. The stock has a ‘Strong Buy’ ranking on TradingView with 17 verticals in favour, eight neutral and one sell.

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Securities Disclosure: I, Bala Yogesh, hold no direct investment interest in any company mentioned in this article.

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