6G Network Anomaly Detection in Task Offloading and Scheduling in Multi-Robotic Path Planning Communication Based Ids Network Using Quantum Machine Learning and Liquid Neural Network

Abstract

With the continuous advancements in communication technology and the emergence of multirobotic path planning, the need for efficient task offloading and scheduling mechanisms has become paramount. The development of 6G networks offers unprecedented opportunities for improving communication capabilities, yet also brings forth new challenges in ensuring network security. Anomaly detection in such networks is crucial to safeguard against potential threats and disruptions.In this research, we propose a novel approach to address the challenges in task offloading and scheduling in multirobotic path planning while simultaneously enhancing network security through the use of Quantum Machine Learning (QML) and Liquid Neural Networks (LNNs). The integration of quantum computing principles and liquid-based neural networks enables us to leverage the strengths of both paradigms, enhancing the efficiency and accuracy of the proposed system.The key focus of this study is on the development of a communication-based Intrusion Detection System (IDS) utilizing the unique properties of quantum computing to efficiently process and analyze large-scale network data. By harnessing the power of quantum entanglement and superposition, the IDS becomes capable of detecting anomalies and potential threats with exceptional precision, even in complex and dynamic multirobotic path planning scenarios.The effectiveness of the proposed 6G network anomaly detection system is evaluated through extensive simulations and real-world experiments. The results demonstrate that the integration of QML and LNNs significantly improves the efficiency and reliability of task offloading and scheduling in multirobotic path planning while providing robust and accurate intrusion detection capabilities. The research contributes to the advancement of quantum-based artificial intelligence applications in communication networks and robotics, opening up new horizons for secure and efficient multirobotic systems.