Owned by Statistics: Using Kubeflow to Defend vs Attacks on Your ML Models

November 18, 2020

November 18, 2020 @ KubeCon + CloudNativeCon North America Boston 2020

Machine learning continues its spread across the tech world and is now in use by more than 80% of enterprises world wide.

However, with the increased reliance on this technology, the spectre of additional security attack surface areas rises up. Machine learning attacks are a new area of opportunity for adversaries, and require a new way to approach defense.

In this talk, we will cover several of the most common ML attacks today and how to defend against them. We will also show how to use a sophisticated, cloud-native pipeline with Kubeflow will to enable organizations to detect, remediate and defend against future attacks.


David Aronchick

David Aronchick

Head of OSS ML Strategy @ Microsoft

David leads Open Source Machine Learning Strategy at Azure. This means he spends most of my time helping humans to convince machines to be smarter. He is only moderately successful at this. Previously, he led product management for Kubernetes on behalf of Google, launched Google Kubernetes Engine, and co-founded the Kubeflow project.

Yannis Zarkadas

Yannis Zarkadas

Software Engineer

Yannis is a software engineer at Arrikto, working with Kubeflow and the Kubernetes sig-storage group. He loves contributing to open source projects and has authored the Cassandra Operator in Rook and the official Scylla Operator, which he is currently maintaining.

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