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FortiWeb Web Application Firewall Furied With Machine Learning Capabilities

Upgraded FortiWeb Web Application Firewall Two-step AI-based Machine Learning Improves Attack Detection Accuracy to Create a Nearly “Set and Forget” Web Application Firewall

Fortinet announces tweaks its FortiWeb Web Application Firewall (WAF) software upgrading to 6.0. The new FortiWeb WAF is said to make it the only major WAF security vendor to use machine learning for behavioral-based threat detection in web applications.

Traditionally, WAFs have relied on application learning (AL) for anomaly and threat detection, but in today’s dynamic threat landscape, AL has proven to have limitations that lead to false positive attack detections and require a significant amount of time to manage for already bogged down security teams.

The newly introduced capabilities in the FortiWeb Web Application Firewall touts to address these issues by introducing machine learning capabilities for better threat detection, faster response times and easier management.

Unlike AL, which uses a one-layer approach to detect anomalies based on simply matching inputs to what it has observed and treating every variation as a threat, FortiWeb now uses a two-layer approach of AI-based machine learning and statistical probabilities to detect anomalies and threats separately.

The first layer builds the mathematical model for each learned parameter and then triggers anomalies for abnormal requests. The second will then verify if the anomaly is an actual threat or if it is a benign variance (false positive). These new innovations allow FortiWeb to provide nearly 100 percent application threat detection accuracy while requiring virtually no resources to deploy and finetune settings.

Rajesh Maurya, Regional Vice President, India & SAARC, Fortinet, said, “With a staggering 48 percent of data breaches being caused by hacking web application vulnerabilities, it’s clear that cybercriminals are increasingly 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. Fortinet has combined our advanced AI-based machine learning capabilities with our FortiWeb WAF to protect web-based applications from attacks targeting known and unknown exploits with near 100 percent threat detection accuracy. It also benefits from automated management and seamless integration with the Fortinet Security Fabric.”

Further bolstering Fortinet’s WAF offering, FortiWeb leverages nearly six years of AI and machine learning development from FortiGuard Labs for its threat detection services and integrates seamlessly into the Fortinet Security Fabric to defend against sophisticated threats that evade other technologies or slip between the gaps of point-based solutions. FortiWeb is available in four convenient form factors including hardware appliances, virtual machines for all the major hypervisor platforms, public cloud options for AWS and Azure, and a hosted cloud-based solution.

“Fortinet and TNP have been our network security partners for many years. As the threats have continued to evolve, especially with the increase in the use of web-based business applications, we have found the Fortinet Security Fabric products, including FortiWeb, have helped us to quickly adapt and meet new challenges. The fact that all Fortinet solutions talk to each other to quickly identify and block an attack saves us significant time and resources, as well as enabling a faster response. This approach is now more important than ever as we increasingly see more sophisticated and automated attacks,” said Tony Doyle, Head of ICT Services, Blackpool Council.


Niloy Banerjee

A generic movie-buff, passionate and professional with print journalism, serving editorial verticals on Technical and B2B segments, crude rover and writer on business happenings, spare time playing physical and digital forms of games; a love with philosophy is perennial as trying to archive pebbles from the ocean of literature. Lastly, a connoisseur in making and eating palatable cuisines.

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