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Revealing CNN Architectures via Side-Channel Analysis in Dataflow-based Inference Accelerators
The proposed attack exploits spatial and temporal data reuse of the dataflow mapping on CNN accelerators and architectural hints to recover the structure of CNN models.
Breaking On-Chip Communication Anonymity using Flow Correlation Attacks
We show that the existing anonymous routing is vulnerable to machine learning (ML) based flow correlation attacks on NoCs.
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