Traditionally, a threat was detected, and a remediation plan was deployed. This is classic Endpoint Detect and Response (EDR). Would that life be that easy.

Today, we have malicious actors using generative Artificial Intelligence to slightly alter code, so it doesn't resemble previous attacks. This kind of eliminates the "detection" part of EDR.

This isn't rare anymore. In fact, in August of 2023 Deep Instinct did a study where it concluded that there was a significant increase in cybersecurity attacks fueled by generative Artificial Intelligence. Some findings

· 75% increase in attacks last year

· 85% if these attacks are attributed to generative Artificial Intelligence

During today's interview, Carl Froggett from Deep Instinct gives an option to run-of-the-mill EDR. He gives the listeners an overview of how Deep Instinct started. He explains that, originally, they relied on open source for data on attack activity. However, researchers discovered that open source was not powerful enough.

Deep Instinct decided to develop proprietary ways to look at massive data streams to determine if there were threats. They started with Artificial Intelligence, moved to Machine Learning, and focused on the algorithm associated with a concept called Deep Learning. They have had tremendous success.

One determinate of effective threat screening is reducing false positives. This is a significant problem. In the interview, Carl Froggett suggests that if an organization has 30,000 events a day and just 1% are false positives, this can be a massive drain on work for cyber professionals.

When your opponent uses Artificial Intelligence then you must respond in kind; learn how Deep Instinct can assist your agency in today's brave new world.

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