148 citations · 249 across the 20 of their papers we have counts for
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Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis +7
The success of machine learning is fueled by the increasing availability of computing power and large training datasets. The training data is used to learn new models or update exi…
Machine Learning Security against Data Poisoning: Are We There Yet?
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis +3
The recent success of machine learning (ML) has been fueled by the increasing availability of computing power and large amounts of data in many different applications. However, the…
Energy-Latency Attacks via Sponge Poisoning
Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio +2
Sponge examples are test-time inputs optimized to increase energy consumption and prediction latency of deep networks deployed on hardware accelerators. By increasing the fraction…