Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data
Gorka Abad
Network and Distributed System Security (NDSS) Symposium 2024 · Day 3 · ML Security & Privacy
Deep Neural Networks (DNNs) have revolutionized machine learning, yet their computational demands and energy consumption pose significant challenges, particularly for resource-constrained applications. Spiking Neural Networks (SNNs) emerge as a promising alternative, offering substantial energy efficiency gains—up to 12.2 times better compute energy efficiency in some studies—and biologically plausible data processing. SNNs are uniquely suited for **neuromorphic data**, which is captured by specialized Dynamic Vision Sensors (DVS cameras) that record per-pixel brightness changes asynchronously, enabling low power consumption, low latency, and high temporal resolution crucial for domains like autonomous driving and medical diagnosis.