Web: http://arxiv.org/abs/2207.01991

Nov. 22, 2022, 2:20 a.m. | Sebastian Szyller, N. Asokan

cs.CR updates on arXiv.org arxiv.org

Nowadays, systems based on machine learning (ML) are widely used in different
domains. Given their popularity, ML models have become targets for various
attacks. As a result, research at the intersection of security/privacy and ML
has flourished. Typically such work has focused on individual types of
security/privacy concerns and mitigations thereof. However, in real-life
deployments, an ML model will need to be protected against several concerns
simultaneously. A protection mechanism optimal for one security or privacy
concern may interact negatively …

machine machine learning machine learning models protection

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