When someone says the word hurricane, I hear the shrill weather-alert warning sound in my head. Having grown up in Florida and now living in North Carolina, I’ve been through many hurricanes and have the routine down — stock up on supplies and hurricane snacks, bring in the patio furniture, fill up the cars with gas and hunker down until it passes or shifts direction.
But it’s the jarring sound of the National Weather Service alerts that always send my stress levels up. And over the years, I’ve come to realize it’s because I have no idea what the sound means for my family. That’s how alert fatigue works on a job, as well.
Sometimes it’s simply the 437th reminder of a hurricane warning, at which point I’m more than well aware of what’s going on. Other times, it’s a flash flood alert for an area hundreds of miles from my house. Sometimes, it’s a tornado alert — which is a serious threat during a hurricane, even for inland folks like us. But even then, I have to stop, process and sometimes consult a map. From there, I can figure out if we need to head for the closet because the tornado has my home in its sights or not. At some point, someone turns the sound off so we aren’t constantly jumping. Then I worry that because of alert fatigue we are going to miss a critical tornado alert.
Cybersecurity experts tell me they go through the same issues in terms of cybersecurity alerts — struggling to figure out which alerts pertain to their company and which are not relevant. And even more importantly, what actions they need to take to keep their company safe. Research backs up my anecdotal findings: a report from FireEye found that one-third of analysts ignore alerts when their queue is full. And 87% share the same concern as I do during a hurricane — they worry about missing incidents.
Using AI to Reduce Alert Fatigue
Organizations are turning to artificial intelligence (AI) more and more to help analysts sort through the alert noise. The report also found that two in five analysts are now using a mixture of AI and machine learning (ML) with SOAR tools and SIEM software. By using these technologies, analysts receive a personalized list of the alerts that need their attention.
By using AI, analysts spend less time on alerts that are either low level or not relevant to their company. This means they can often prevent damage by acting quicker on important alerts. While the analysts still make the final decision in terms of triage, AI does the first pass, in addition to suggesting custom fixes for the analyst’s specific tasks. What’s more, analysts can now focus on proactive and inventive projects. These can reduce risk, which after all is the purpose of the work. It means they don’t spend most of their days reacting to known issues.
Instead of analysts managing threats through their email inbox, as happens when relying on alerts, AI puts all threats and remediation on a single dashboard. Displays without this only locate a potential problem. This takes it a step further and automates the investigation and even the integrated response. It provides the quick resolution of many threats, which reduces alert fatigue.
How SIEM Software Helps
Some analysts use SIEM software, which is specifically designed to speed up the detection of events and improve incident response and detection. SIEM starts by checking your infrastructure and systems for potential threats using AI-gained log data.
Through advanced analytics, such as user behavior analytics and network flow insights, SIEM quickly detects behavior that is outside the normal patterns for your networks and systems in addition to concerning external activity. Instead of receiving a multitude of generic alerts, you only receive alerts for behavior that is suspicious for your company, which cuts down on the volume and alert fatigue. Lastly, SIEM triages the alerts based on insights gathered from past incidents and typical usage patterns at your companies. Using SIEM instead of manual responses, many companies see major improvement in both threat resolution and speed.
Another option for reducing alert fatigue and improving incident management is SOAR, which focuses on three key areas: threat and vulnerability management, incident response and security operations automation. SOAR is a newer technology than SIEM. It uses many of the same concepts as SIEM but also uses external data from third parties and other enterprises. In addition, SOAR automates resolution more than SIEM by removing more manual tasks.
However, SIEM products often cost less than SOAR, making SIEM an entry into automated cybersecurity for many companies. In addition, companies without specialized expertise find using SOAR in conjunction with professional services often increases effectiveness. Through the integrated alert and response systems, SOAR technology improves teamwork, communication and consistency across the decision chain, which leads to improved responses.
Using AI to Reduce Alert Fatigue
While making the decision to use AI is the first step towards improving your cybersecurity threat protection and response, your company must also evaluate the overall identification and response process as part of the shift. With a traditional approach, the response is spread over multiple systems and analysts. AI brings it all together. By reviewing your end-to-end processes and adding AI tools into the process instead of on top of your workflow, you can reduce alert fatigue.
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