We propose the development of a system that uses the TensorFlow Quantum and PennyLane packages and applies quantum machine learning (QML) algorithms to process various security and malicious data sets and compares the performance with classical machine learning (CML) algorithms. One of the most important applications of QML is for cybersecurity. This project will begin with research of quantum computing and machine learning, then followed by the development of a system that uses the TensorFlow Quantum and PennyLane packages and applies quantum machine learning (QML) algorithms to process various security and malicious data sets and compares the performance with classical machine learning (CML) algorithms.The data sets for our modules include DDoS prevention, malware detection, user behavior anomaly detection, and spam email filtering. We provide detailed instructions for program implementation on our project website in order to better proliferate quantum programming in order to encourage others to explore quantum algorithms
