As IT environments become more dynamic, hybrid, and complex, it’s becoming increasingly difficult for security operations center (SOC) teams to quickly detect and address critical threats with traditional tools.
SOC staff must process and analyze a massive—and growing—amount of data, as they face ever more sophisticated cyber attacks. To respond effectively, SOC leaders can’t keep adding rules-based tools to their already large and often unwieldy security stack.
Instead, they need AI technology that analyzes data at scale and in real time and that uses machine learning to spots any anomalies that could signal a breach. That way, SOC teams detect unknown, fast-evolving threats missed by rules-based products configured to spot known attacks.
Indeed, AI and machine learning have gone from being emerging, nice-to-have technology for cybersecurity to being a must-have among SOCs tasked with protecting digitally transformed IT infrastructures from today’s barrage of advanced and devastating cyber threats.
Here are three ways in which AI and machine learning can make your SOC team faster, more productive, and more effective—and boost the cyber resilience of your company.
1. Help close the talent and budget gaps
Cybersecurity departments, and SOC teams in particular, have struggled for years to find qualified staffers and to receive adequate funding. Simultaneously, the number and sophistication of attacks have increased. Fortunately, AI and machine learning can help cybersecurity leaders in direct, concrete ways with these talent and budget challenges.
By streamlining and automating tasks such as security data collection, correlation, and analysis, AI and ML technology frees SOC teams from time-consuming, arduous manual work, so they can focus on higher-level and more valuable tasks.
In this way, staffers can work smarter and be more productive, reducing the need to hire more people, especially at a time when it’s harder to find candidates in the security domain with the necessary skills and experience. AI technology becomes a workforce multiplier by not only taking over tasks, but also performing them more quickly and with more accuracy and precision.
Likewise, the adoption of AI and ML technology allows SOC teams to retire legacy tools that no longer serve the team well, and thus consolidate the security stack, lowering costs and freeing up money in the budget for other needs, such as staff training and modern products.
2. Level the playing field
SOC teams are engaged in a competition against cyber criminals that’s thoroughly unfair. For starters, there are way more bad guys than there are defenders. Then there’s the crushing reality that the bad guys have an unlimited number of tries in this game, and they only need to score once to win. For security pros, the opposite is true: They must stop every attack, or else they lose. In other words, the scales are tipped in favor of the malicious hackers.
Here again, AI and ML make a big difference. By weaponizing mathematics and data science, you can suddenly make the fight a bit more even—or at least less lopsided. You’re no longer fighting with one hand tied behind your back.
You incorporate AI and ML tools into your team, and use them for what they do best: continuous ingestion and processing of mounds of security data at lightning speed, giving you full visibility into your threat posture.
With AI and ML, the SOC team gets access to better, more complete data, richer context, and deeper insights to make decisions and respond to threats. No more manual correlation, false positive floods, and information overload. The result: faster threat discovery, quicker problem diagnosis, and more effective and precise response, regardless of the complexity and size of your IT environment.
3. Switch from reactive to proactive
Cyber criminals are leveraging all the latest technology in order to sharpen their attacks. They’re using adversarial networks. They’re familiar with threshold poisoning techniques. In some ways, they are using technology much more efficiently than the defenders are.
You must respond in kind and take advantage of any technological advantages available to you. AI and ML are a no-brainer. They’ll give an immediate boost to your cyber resiliency and help you elevate your defenses, making you more proactive and nipping threats in the bud, before they progress to full-blown breaches.
In particular, you’ll be better able to flag the latest attack vectors early, even new ones you’re unaware of that can only be detected through the pattern- and anomaly-detection capabilities of AI and ML.
Outwit, outplay, outlast
Considering what we’re up against, I can't imagine how we will be able to survive without using AI and ML. I don't think we have a choice. Otherwise, we’ll be in a compromised position, where we’re always in reactive, defensive mode, always one step behind, and that’s a no-win scenario.
Keep learning
Learn from your SecOps peers with TechBeacon's State of SecOps 2021 Guide. Plus: Download the CyberRes 2021 State of Security Operations.
Get a handle on SecOps tooling with TechBeacon's Guide, which includes the GigaOm Radar for SIEM.
The future is security as code. Find out how DevSecOps gets you there with TechBeacon's Guide. Plus: See the SANS DevSecOps survey report for key insights for practitioners.
Get up to speed on cyber resilience with TechBeacon's Guide. Plus: Take the Cyber Resilience Assessment.
Put it all into action with TechBeacon's Guide to a Modern Security Operations Center.
