New Attack Method Breaks Security Of Brain-Inspired AI Networks
SNNs thought to be secure against adversarial attacks but researchers found a new 'BIS' attack breaks them using hidden training backdoors
This is a Plain English Papers summary of a research paper called New Attack Method Breaks Security of Brain-Inspired AI Networks Using Hidden Training Backdoors. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter. Overview SNNs (Spiking Neural Networks) can resist adversarial attacks better than traditional neural networks Researchers discovered surrogate gradients make SNNs vulnerable to attacks A new "BIS" attack breaks these invisible surrogate gradients BIS attack is more effective and uses fewer perturbations than existing methods The atta...