With machine learning becoming increasingly popular, one thing that has been worrying experts is the security threats the technology will entail. We are still exploring the possibilities: The breakdown of autonomous driving systems? Inconspicuous theft of sensitive data from deep neural networks? Failure of deep learning–based biometric authentication? Subtle bypass of content moderation algorithms? Meanwhile, machine learning algorithms have already found their way into critical fields such as finance, health care, and transportation, where security failures can have severe repercussion. Parallel to the increased adoption of machine learning algorithms in different domains, there has been growing interest in adversarial machine learning, the…
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