ML Model Poisoning: How It Happens and Detection

Data poisoning is a growing threat that undermines machine learning models by injecting malicious training examples. Attackers use diverse techniques, making it essential for organizations to anticipate evolving strategies. Detecting poisoned data is challenging but achievable by combining detection techniques with traditional cybersecurity measures like securing stored data.