Software developers and cyber security experts have long fought the good fight against vulnerabilities in code to defend against hackers. A new, subtle approach to maliciously targeting machine learning models has been a recent hot topic in research, but its statistical nature makes it difficult to find and patch these so-called adversarial attacks. Such threats in the real-world are becoming imminent as the adoption of machine learning spreads, and a systematic defense must be implemented.
Originally from KDnuggets https://ift.tt/2MezULS
source https://365datascience.weebly.com/the-best-data-science-blog-2020/machine-learning-adversarial-attacks-are-a-ticking-time-bomb
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