Smart Intelligent Control Application Using Quantum Computation and Machine Learning

Machine learning (ML) is significantly transforming and modernizing urban areas by enhancing service quality across various sectors such as transportation, security, robotics, healthcare, energy, and finance." Even with their overwhelming success, machine learning (ML) algorithms still require significant computational work with fast computer hardware in order to handle model complexity and guarantees that result in effective, dependable, and robust solutions. Regarding cyber security and digital protection, quantum computing (QC) is a formidable contender to assist machine learning (ML) systems achieve optimal performance. "This research aims to develop the Quantum Adaptive Neuro-Fuzzy Inference System (QANFIS) model for detecting distributed denial of service attacks in smart control applications. The usefulness of our proposed model is demonstrated by evaluating it against an actual dataset of denial of service attack incidents. Lastly, various unresolved problems and difficulties with fitting ML with QC are discussed along with the findings.