Journal article
No Stable Self: What Self-Referential Anomaly Defence Can Certify for a Continually Learning System, Why Every Located Guarantee Holds the Benign Distribution Still, and Why Immunology's Own Answer Is a Damage Signal From Outside
Immune-inspired security proposes that a system can protect itself by learning what it normally is and treating departures from that as threats. Continual learning makes departure the normal case: the system is supposed to change, so a poisoning campaign and a legitimate shift in the data both…