What Is the Role of AI in Cybersecurity Operations?
By Tony Bradley
There’s a lot of hype around artificial intelligence (AI). It seems like every technology and cybersecurity vendor these days is claiming to use AI in some way, shape, or form. AI is not a magical solution for every problem, but one area where AI—more specifically machine learning (ML)—can play an essential role is in the area of cybersecurity operations.
How Our Machine Learning Works
Machine learning is a subset of artificial intelligence that enables computers to learn without being programmed. It leverages large volumes of data to help the computers understand patterns and make decisions. It’s important to note that not all machine learning is created equally, though. Machine learning output is only as good as the volume and quality of data supplied and the algorithms applied to analyze the data.
At Alert Logic, data scientists curate and label the high volume of security data and machine telemetry that we collect from our customers around the world. This provides the training data for our machine learning algorithms to produce high confidence security outcomes. Our product engineering team develops scalable, production-quality detection for the techniques that the data scientists develop, and our application security experts and SOC (security operations center) analysts provide feedback to confirm and improve the findings.
Each part of our supervised machine learning is closely linked. Collecting high-quality, consistent data is critical. If the data is noisy, the system will train incorrectly and produce bad results. Once the algorithm is trained, the real-world data is measured and collected using our own sensors in customer environments.
Using machine learning provides a variety of benefits for Alert Logic and our customers.
AI Is an Essential Force Multiplier
Organizations have limited cybersecurity resources. The industry is faced with a dramatic shortage of cybersecurity professionals with the necessary knowledge and skills, but there would still be limited resources even if that were not the case. Even Fortune 100 corporations with massive budgets and extensive cybersecurity teams still have a limit to how far those resources can go.
Artificial intelligence acts as a force multiplier to extend those resources. Machine learning and artificial intelligence can be applied to automate some of the routine tasks associated with monitoring network traffic and log analysis—effectively augmenting the efforts of the cybersecurity team.
Cybersecurity at the Speed of the Cloud
AI also plays a crucial role in the ability to effectively monitor for threats in a complex, hybrid cloud environment while faced with an expanding and evolving threat landscape. AV-Test registers an estimated 350,000 new malicious programs and potentially unwanted applications every day.
Organizations need to be able to detect and defend against these emerging threats across local data centers and cloud platforms. The complex ecosystem, DevOps culture, and container technologies combine to create a dynamic environment that can expand and contract dramatically as demand rises and falls. It’s virtually impossible for any human cybersecurity professional—no matter how good—to match the pace or scale necessary to effectively monitor such an environment.
Focus on What Matters
The net result of using AI in cybersecurity operations is that your IT and cybersecurity teams can provide more value. Leveraging AI for cybersecurity operations frees up security professionals to focus on high priority tasks and proactive measures to improve cybersecurity overall.
For Alert Logic customers, it means more streamlined and effective monitoring from our SOC analysts. Machine learning helps us separate the signal from the noise at scale so we can invest our time investigating security events that require human attention rather than chasing down false positives.
There is still a lot of hype and confusion about artificial intelligence and machine learning, but when utilized properly they make a significant difference in an organization’s ability to keep up with the pace of threats and implement effective cybersecurity.