How AI in Cybersecurity Addresses Challenges Faced by Today’s SOC Analysts

How AI in Cybersecurity Addresses Challenges Faced by Today’s SOC Analysts

Today’s security operations centers (SOC) have to manage data, tools and teams dispersed across the organization, making threat detection and teamwork difficult. There are many factors driving complex security work. Many people now work from home with coworkers in far-away places. The cost and maintenance of legacy tools and the migration to cloud also make this more complex. So do hybrid environments and the multiple tools and vendors in use. Taking all these factors into account, the average analyst’s job has become more difficult than ever. Often, tracking down a single incident requires hours or even days of collecting evidence. That’s where artificial intelligence (AI) in cybersecurity comes in.

Analysts might spend a lot of time trying to gather data, sifting through gigabytes of events and logs and locating the relevant pieces. While they try to cope with the sheer volume of alerts, attackers are free to come up with ever more inventive ways of conducting attacks and hiding their trails.

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What AI in Cybersecurity Can Do 

AI makes the SOC more effective by reducing manual analysis, evidence gathering and threat intelligence correlation — driving faster, more consistent and accurate responses.

Some AI models can tell what type of evidence to collect from which data sources. They can also locate the relevant among the noise, spot patterns used in many common incidents and correlate with the latest security data. AI in cybersecurity can generate a timeline and attack chain for the incident. All of this leads the way to quick response and repair.

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