Keynote “Hacking AI – the Cybersecurity Challenge in AI Industry”
By Mirko Ross
CEO asvin
Abstract:
Data Poisoning: Recognizing the Poisoned Apple and Mitigating Risks for ML Applications
ML models are only as good as the quality of the data and its classification when trained. This creates a host of new options for attackers to influence models in a desired direction through targeted data contamination – also known as data poisoning.
This situation is complicated by the complexity of ML applications and architectures in practice. In addition to the large attack surface within the system architecture, there are also numerous points where data can become the poisoned apple for ML models and training due to disruptions in the data supply chain.
The presentation will use practical examples to show the points of attack for data poisoning and provide advice on how to minimize the risk.
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