Nicholas Boucher is a PhD at Cambridge University where his focus is on security including on topics like homomorphic encryption, voting systems, and adversarial machine learning. He is the lead author of a fascinating new paper – “Bad Characters: Imperceptible NLP Attacks” – which provides a taxonomy of attacks against text-based NLP models, that are  based on Unicode and other encoding systems.

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