Quantum Machine Learning Driven Malicious User Prediction for Cloud Network Communications

This letter proposes a novel malicious user prediction model based on quantum machine learning that estimates the vicious entity present in communication system precedently before allocating data distributed environments. The proposed scrutinizes behavior of each and probable breaches using developed predictor unit. computes essential scores associated with request for process unit by generating training samples. exploits computational behavioral properties Qubits Quantum gates accurate high precision to grant access non-malicious requests only. experimental evaluation comparison state-of-the-art methods reveal it significantly improves security up 33.28%.