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Speeding Up Response Times in the SOC with AI

Speeding Up Response Times in the SOC with AI

For a while, it seemed like there could only be one: a well-staffed Security Operations Center (SOC) or a robotic, AI-driven solution set replacement. Why not both?

Before the usual barrage of questions and counterarguments, let’s establish that there obviously is some crossover between what SOCs currently do and what AI will take on. That’s very much the point, although it doesn’t have to mean the end of an era (SOCs are here to stay). But it may mean the end of that era struggling with slow, a key debilitating factor in the race against cybercrime.

Artificial intelligence (AI) is being used to speed up SOC response times and introduce SOC staffers to a whole new generation of productivity.

Here’s how it works.

Why “Slow” Kills a SOC

It takes an average of 194 days (or about three and a half months) to detect a data breach, and every second counts.

As Verizon notes, “A longer mean time to detect a breach, or MTTD, means more opportunity for cyber criminals to steal data, extend their reach across the network or achieve persistence and escalate their privileges.” It’s no surprise that security researchers have confirmed that the longer a breach takes to detect and contain, the higher the overall cost will be.

How Does AI Help Speed SOC Response Times?

According to IBM’s 2024 Cost of a Data Breach Report, organizations that extensively used security AI and automation in prevention saved an average of $2.22 million in potential data breach costs. Here’s how AI removes those stumbling blocks that slow SOCs down.

1.    Alert correlation

SOCs are faced with so many alerts that they are forced to ignore no less than 62% of them, research reveals.  AI can analyze multiple telemetries and bring together data from disparate parts of your network to correlate alerts and provide additional evidence to identify valid ones. The faster SOCs know which notifications to chase after, the faster those underlying threats will get caught – and the less time SOCs will waste sifting through false alarms.

2.    Advanced threat detection

It’s no secret that AI-infused technology can spot signs of bad behavior that traditional tools (fewer and farther between now) can’t catch. Thanks to obfuscated code, polymorphic malware, insider threats, and the low-and-slow attacks of embedded threat actors, these threats can take a long time to detect. APTs have a particularly long dwell time, and all the while, threat actors are exfiltrating valuable data and pilfering sensitive secrets.

By being quick to spot the tell-tale signs of attacks, AI-driven tools can alert SOCs to these hidden threats sooner and hasten the time to respond. Plus, with the addition of machine learning, AI-based solutions can get better at detecting those kinds of attacks every time, learning from the ones before them, and being even quicker to spot them in the future.

3.    Finding Shadow Data

The IMB 2024 Cost of a Data Breach report notes that one in three breaches involve shadow data, proving that “the proliferation of data is making it harder to track and safeguard.” In today’s digital enterprise, there are countless places in which sensitive information could fall through the cracks: think of multi-cloud, hybrid, and remote environments with various repositories, SaaS apps, messaging platforms, and emails in which data could hide.

While finding shadow data seems like more of a proactive measure, knowing where your data resides – all of it – can effectively reduce SOC response times by placing security guardrails and triggers around that sensitive data once it is found. AI-infused tools not only discover but classify and protect shadow data (not so shadow anymore).

Now that that data is accounted for and protected by the organization’s security policies, a threat actor is less likely to secretly find and exploit it—a feat very easy to do when no one in the organization knows it exists.

A Better, More Efficient Breed of SOC Analysts

While AI might be taking a few jobs from SOCs, they are only the jobs that SOCs would likely want to be taken. Security analysts were hired for their expertise, not their ability to perform repetitive tasks, gather data en masse, or endure tedious stretches of vetting false positives. That is what technology is for, and AI (boosted with automation) simply performs those jobs at a scale unimaginable by humans alone.

As noted by security expert Grant Oviatt, “With routine tasks automated, analysts can dedicate their skills to areas requiring human intuition and expertise—like developing advanced security protocols and engaging in proactive threat hunting.” Now, SOCs can spend less time reacting and more time doing those “luxury” tasks they often never have time for; proactive planning, security strategizing, and overall optimization. In short, AI-performed tasks give SOCs a chance to shine.

And to do what they do best: make complex, critical decisions that no piece of technology is qualified to make.

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