Learning Objectives
Understand why the phase change in cybersecurity requires a holistic, new approach Understand how AI / ML can appropriately be applied to today’s cybersecurity challenges Learn how to assess what AI / ML tools will actually improve your specific cybersecurity posture_We are living in a watershed moment. There is an ongoing shift in cyber threats, both in terms of the adversaries themselves and the environment to be secured. Developing a new approach to security is arguably not only the most important technological issue, but also the most important geopolitical issue of our time.
Everyone is racing to apply artificial intelligence, machine learning, deep learnings, and {insert the buzzword du jour here} to cybersecurity, but they are still failing to slow down and/or stop adversaries. AI is merely translating a business problem into a math problem, so the question should not be “how complicated is the math that you are using?”, but rather “what question are you answering with the math?”
When applied correctly, machine learning can uncover subtle and high-value cybersecurity threats that typically disappear into the noise of corporate networks; when applied incorrectly, it merely buries analysts in more alerts and false positives.
This presentation will address how to strategically frame the challenges in order to harness the power of AI to force-multiply the impact of human security analysts. There are high-risk cross-data-source patterns in your network that you can’t see today. Even if you had 1,000 more human analysts, you wouldn’t be able to find adversaries systematically at enterprise scale. Therefore, the only way forward is to strategically apply AI on integr ...
Central Park East - 6th Floor HACK NYC 2018 events@magegroupe.comLearning Objectives
We are living in a watershed moment. There is an ongoing shift in cyber threats, both in terms of the adversaries themselves and the environment to be secured. Developing a new approach to security is arguably not only the most important technological issue, but also the most important geopolitical issue of our time.
Everyone is racing to apply artificial intelligence, machine learning, deep learnings, and {insert the buzzword du jour here} to cybersecurity, but they are still failing to slow down and/or stop adversaries. AI is merely translating a business problem into a math problem, so the question should not be “how complicated is the math that you are using?”, but rather “what question are you answering with the math?”
When applied correctly, machine learning can uncover subtle and high-value cybersecurity threats that typically disappear into the noise of corporate networks; when applied incorrectly, it merely buries analysts in more alerts and false positives.
This presentation will address how to strategically frame the challenges in order to harness the power of AI to force-multiply the impact of human security analysts. There are high-risk cross-data-source patterns in your network that you can’t see today. Even if you had 1,000 more human analysts, you wouldn’t be able to find adversaries systematically at enterprise scale. Therefore, the only way forward is to strategically apply AI on integrated data to automate expert insight at scale.
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The Critical Infrastructure Association of America, Inc. is a 501(c)6 Not for Profit. The mission of Critical Infrastructure Association of America is to create a membership-based, trade association of like-minded cybersecurity and closely related industry professionals that work in the field of cybersecurity. The goal is to share best practices, establish and maintain high operational standards and to educate and interact with those in the cybersecurity community within public, private and governmental sectors.
