Hidden Threat In Training Set: How Poisoned Data Can Hijack Your AI

Data poisoning is done when attackers tamper with the training data employed in constructing AI models.

Imagine training a facial recognition system with images that have been subtly altered. The model might learn to misidentify individuals or, worse, fail to recognise certain demographics altogether.

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By Krishna Bhatt The industry of today is founded on artificial intelligence (AI), and it is no longer science fiction. AI systems are making life-or-death decisions every day, from diagnosing disease to preventing financial crime. Data poisoning, though, is an increasing threat hiding behind this technological revolution. This silent attack damages AI models in their foundation, making them untrustworthy and even hazardous to implement. Identifying and preempting this risk has become