In a study by IDC, it was found that the global cybersecurity market was worth $107 million in 2019 and is poised to grow up to $151 million by 2023. While most of this expenditure is towards designing software and hardware for protecting systems from hacking or compromising networks, an area which is often overlooked is the integrity of the data being used to train the datasets used by the machine learning algorithms. This is called the poisoning attack, where the intruder injects false training data to corrupt the learning model itself. It could become a significant attack that can undermine the AI systems, businesses and processes built around them.
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