Data Poisoning
Data poisoning is a type of attack where adversaries inject corrupted, misleading, or malicious data into machine learning training datasets. This contamination can cause AI models to learn incorrect patterns, make biased decisions, or fail to detect threats. Data poisoning attacks are particularly concerning in security systems, content moderation, and automated decision-making processes where compromised models can have serious consequences.
What is Data Poisoning?
Data poisoning is an attack technique where malicious actors inject corrupted or misleading data into machine learning training datasets. This contamination can compromise AI models, causing them to make incorrect predictions or fail to identify threats. Data poisoning is closely related to bot contamination, where automated traffic pollutes datasets used for analytics and machine learning.
Prosopo helps prevent data poisoning by blocking malicious bots and ensuring clean, authenticated traffic reaches your applications and data collection systems.