Automatically Prevent, Detect, and Respond to Cyber Threats
Managing security, regardless of the size of the organization, has always been a complicated task. This is usually the result of a number of factors, ranging from not having enough skilled people on the IT staff to analyze the data to simply having too much data to analyze. The result, however, is that threats get missed, or they get discovered too late to do anything about them but clean up the mess.
The Challenge of Complexity
Complexity can be broken down into four key challenges:
Too Many Vendors: The first challenge is the result of vendor and solution sprawl. For decades, the answer to any new security problem was to stick yet another specialized security tool in the wiring closet. In one recent study, 14% of responding CISOs indicated that they had solutions from more than 20 different security vendors installed in their networks, and 3% indicated that they had more than 50. Unfortunately, most of these products were never designed to communicate with each other, which means they also have no ability to create automated workflows or coordinate policy changes. And as networks become increasingly complex through things like digital transformation, and the number of vendors in place continues to increase, valuable threat intelligence is more likely than ever to get lost in the noise.
Too Many Alerts: A related problem is that each of these devices also generates alerts. In the same study cited above, 35% of organizations see between 10,000 and a staggering 500,000 alerts every day that need to be tracked down and confirmed. And since less than 1 in 4 investigated alerts turn out to be legitimate, it is an enormous tax on an already overburdened IT staff.
Manual and Slow Response: To make matters worse, 79% of respondents said that it was “somewhat or very challenging” to orchestrate alerts from multiple vendors, meaning that correlating alerts, log files, and other threat intelligence – often in completely different formats – has to be done by hand. As a result, threats are detected late and responses are often incomplete. It’s part of the reason why the average mean time to identify a threat is nearly 200 days, and requires another nearly 10 weeks to contain a breach.
Lack of Trained Personnel: Compounding these problems further is the ongoing cybersecurity skills gap. There simply aren’t enough people with the general security skills necessary to manage and maintain all of the point products in place, let alone the highly prized security analysts needed to identify, process, and orchestrate an effective response to complex threats.
Machine Learning AI-Driven Security Operations Eliminate Complexity and Reduce Overhead
Fortunately, this is where technology is able to step in. Machine Learning (ML) and Artificial Intelligence (AI) are being rapidly adopted by organizations to perform mundane tasks that bog down security teams, such as correlating log files or performing device patching and updating. But while offloading such tedious tasks from your security staff is beneficial, it is a lot like using a race car to plow a corn field.
Fortinet’s ML and AI-driven Security Operations go well beyond the simple tasks most intelligent solutions have been designed for. The ML systems woven into our global FortiGuard Labs services, for example, constantly assess new files, web sites, and network infrastructures to identify malicious components of cybercrime campaigns, as well as dynamically generate new threat intelligence that allow organizations to predict and prevent cyberthreats.
This intelligence is then delivered through FortiGuard’s subscription services (anti-malware, web filtering, etc.) available for our threat prevention products, including our flagship FortiGate security platforms. And this same Machine Learning is also built directly into many of our customer-deployed offerings to automatically detect previously unknown attacks that may reach the customer ahead of global threat intelligence updates.
It is also a key element of advanced Expert Systems designed to aggregate, analyze, enrich, and alert on threats culled from the large volume of information received from an organization’s IT and security infrastructure, with the option to orchestrate and/or automate response to improve the efficiency of security operations.
These groundbreaking advances in artificial intelligence (AI) enable the automatic prevention, detection, and response to cyber threats that human resources and siloed management platforms are unable to achieve. AI-driven Security Operations enable organizations to not only manage the sprawling collection of security devices they have in place, but also see and protect the data, applications, and workflows spread across thousands or millions of edges, users, systems, devices, and critical applications.
By building AI functionality directly into Fortinet’s security solutions, they can be integrated and deployed across a highly distributed network in a variety of form factors to create a unified and intelligent Security Fabric. These platforms range from ultra-high performance devices designed for hyperscale data centers and architectures, to virtualized platforms deployed as cloud-native solutions in private and public multi-cloud environments.
By weaving AI across the network through the Security Fabric, organizations not only enjoy comprehensive visibility and protection across all devices, users, endpoints, and environments. Centralized AI-driven Security Operations can also collect, correlate, and communicate across the security fabric to ensure faster and more comprehensive response and remediation than any human-led effort could possibly provide.
As a result, Fortinet customers benefit directly from the advanced artificial intelligence used in our Labs in their own organizations, enabling their cybersecurity systems to act like human cybersecurity professionals, including threat researchers, security analysts, incident responders, and more. This enables the organization to reduce the risk and potential impact of security incidents by blocking more, detecting sooner and responding faster, while also improving the overall efficiency and cost of their security operations.
Fortinet’s AI-Driven Security Operations Puts Organizations Back in Charge
By driving Fortinet’s AI-Driven Security Operations and advanced AI technologies deep into the distributed Security Fabric, organizations are able to significantly enhance their ability to detect and respond to threats and adapt security policies and protocols to network and connectivity changes in real time. This, in turn, amplifies and accelerates the services of on-staff threat researchers and data analysts, enabling them to correlate and process threat intelligence in real time, ensuring that they can more consistently and efficiently keep their organization out of harm’s way.
Don’t miss Fortinet’s upcoming global virtual event for cybersecurity and networking professionals to learn more about our latest product announcements. Sign up here.
Engage in our Fortinet user community (Fuse). Share ideas and feedback, learn more about our products and technology, or connect with peers.
Find out how Fortinet integrates AI and machine learning capabilities across our Security Fabric to detect, identify, and respond to threats at machine speed.
Read these customer case studies to see how Warrior Invictus Holding Co., Inc. and Infosec Partners are using AI to efficiently collect, analyze, and classify cyber threats to protect their networks.
