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WFH-BFs: Dynamic Defense Against DNN Bit-Flips via a Weight Function Hierarchy
DescriptionDefending DNNs against bit-flip attacks (BFAs) typically incurs prohibitive computational overhead, a critical barrier for deployment in safety-critical systems. We challenge this "one-size-fits-all" defense paradigm by introducing the Weight Function Hierarchy (WFH), a framework that deconstructs DNNs into functionally distinct tiers: a compact Anchor Core for foundational representation, a Class-Sensitive layer for decision-making, and a Reservoir for redundancy. Based on WFH, our synergistic framework, WFH-BFs, couples offline preparation with online adaptation. Offline, we differentially harden the Anchor Core while embedding pruning tolerance elsewhere. Online, a lightweight integrity checker safeguards the core, while a dynamic pruning mechanism reconfigures the network to neutralize attacks. Experiments show WFH-BFs increases BFAs cost by 17.5x and maintains near-original accuracy (<1.4% drop) under high-rate random errors. Critically, our dynamic defense achieves this robust security while simultaneously reducing the overall computational load (GFLOPs), breaking the security-efficiency trade-off.