Federated quantum-inspired anomaly detection using collaborative neural clients

The approach allows privacy-preserving anomaly detection across multiple domains and serves as a framework for enlarging and scaling the system. Being quantum-inspired compatible allows for future-proofing and further expediting and enhancing security. The system, having the capability to securely work in a distributed manner, can, thus, be utilized in critical information domains like cybersecurity, finance, and healthcare, where privacy of data is deemed extremely important. This work, thereby, offers a useful federated learning approach towards anomaly detection while going a step further towards the incorporation of quantum computing into secure, distributed AI systems.