Proposals for model vulnerability and security
O'Reilly on Data
MARCH 20, 2019
The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. Data poisoning attacks. To poison data, an attacker must have access to some or all of your training data.
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