Security Properties of Neural Networks as Decision Problems
Certifying a deployed neural network raises decision problems that the verification literature has not classified: whether the model carries a backdoor planted in its training data, whether a fault in its stored parameters can drive it into an unsafe state, whether its output leaks a private part of its input. We formalise eight such problems and classify what we can. The organising observation is a logical one. The function computed by a piecewise linear network, together with all its node values, is definable by a quantifier-free formula of real addition of size linear in the network, so a property of the network is a quantifier-alternation sentence, which Sontag's 1985 theorem places i...
| Authors | Adrian Wurm |
|---|---|
| Primary category | cs.LO |
| Published | 30 September 2026 |
| Last updated at source | 30 September 2026 |
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