Analyzing Cybersecurity Risks with and in Machine learning

Thu 15Apr2021
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Mathias Humbert, Swiss Cyber Defence Campus

From 12:30 until 13:30

At Zoom: https://ethz.zoom.us/j/67860681938

https://ethz.zoom.us/j/67860681938

Abstract:

In this talk, I will first introduce the Cyber-Defence Campus, including its main topics of interest and activities. I will then show with two application examples how machine learning can enable us to analyze and anticipate cybersecurity risks at scale. First, we will see how supervised and unsupervised learning algorithms can help detect intrusions and cyberattacks in the context of IoT networks, and second how supervised learning can help evaluate privacy risks in wearable devices' data, more precisely regarding personality inference. Finally, we will see that machine learning services themselves can be prone to privacy attacks, specifically membership inference attacks, and what we can do against that.

Join the Zoom meeting at 12:30 on Thursday, April 15th: https://ethz.zoom.us/j/67860681938

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