From insiders to sophisticated external attackers, the reality of cybersecurity today is that the threat is already inside. Legacy approaches to cybersecurity, which rely on knowledge of past attacks, are simply not sufficient to combat new, evolving attacks, and no human cyberanalyst can watch so much or react quickly enough. A fundamentally new approach to cyberdefense is needed to detect and respond to these threats that are already inside the network—before they turn into a full-blown crisis.
Justin Fier explains why autonomous response and machine learning is the future of defense and shares the immune system approach to cybersecurity with an overview of the Darktrace Enterprise Immune System, which provides complete network visibility and the ability to prioritize threats to better allocate time and resources. Self-learning systems, which represent a fundamental step-change in automated cyberdefense, are relied upon by organizations around the world and can cover up to millions of devices. Based on machine learning and probabilistic mathematics, these new approaches to security can establish a highly accurate understanding of normal behavior by learning an organization’s pattern of life. They can therefore spot abnormal activity as it emerges and even take precise, measured actions to automatically curb the threat.
This session is sponsored by Darktrace.
Justin Fier is the director of cyber intelligence and analytics at Darktrace. With over 10 years of experience in cyberdefense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems, and Abraxas. He is a highly skilled technical officer and a specialist in cyber operations across both offensive and defensive arenas.
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