CAFBA: Context-aware adaptive fusion backdoor attack for polyp segmentation

Researchers discovered a new type of attack called CAFBA (context-aware adaptive fusion backdoor attack) that can compromise AI models used for polyp segmentation (identifying abnormal growths in medical images). This backdoor attack (a hidden malicious instruction planted in an AI model) tricks the medical AI into making incorrect diagnoses when specific conditions are present, potentially causing serious harm to patients.