Automating Incident Response with Machine Learning

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Presented by

Mike Parkin, Director of Technical Marketing, Gurucul

About this talk

Incident Response is a key responsibility of any SecOps team whether they are sited locally, operating as a distributed group, or a function provided by an MSSP. With the sheer number of incidents they can face, it can be difficult for the team to stay ahead of the game. Fortunately, automation, based on AI-driven security analytics, can lighten the load and make the team more efficient, more effective, and better able to handle their workload. By applying artificial intelligence, the system can adapt and react to new threats even as they're developing. But beyond that, Machine Learning lets the system evolve over time, adjusting itself to the operational environment to optimize performance and efficacy. Join us as we explain how Gurucul's Unified Risk and Security Analytics platform uses machine learning and artificial intelligence to deliver advanced automated incident response.
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Gurucul is a security analytics company founded in data science that delivers radical clarity about cyber risk. Our REVEAL platform analyzes enterprise data at scale using machine learning and artificial intelligence. Instead of useless alerts, you get real-time, actionable information about true threats and their associated risk. The platform is open, flexible, cloud native and cost optimized. Organizations can save 50% or more while achieving complete data control, visibility, searchability, and analytics within a single console. Industry analysts have recognized our platform as a Visionary in the 2024 Gartner(R) Market Quadrant(TM) for SIEM for the third-consecutive year. Our solutions are used by Global 1000 enterprises and government agencies to minimize their cybersecurity risk. To learn more, visit Gurucul.com and follow us on LinkedIn and Twitter.