The tremendous growth in the area of quantum technologies offers significant opportunity for improving cyber security with the help of Explainable Quantum Convolutional Neural Networks (QCNNs). This paper investigates the importance of QCNN models for detecting and mitigating cyber threats in distributed systems. By adding explainability frameworks with quantum methods, we focus on delivering robust threat detection by ensuring transparency in decision-making. This transparency level is crucial for security analysts for better understanding model predictions and alert validate attacks. Our research examines different cyber threats like inside threats and Distributed Denial of Service (DDoS) attacks, by using computational strategy of quantum systems improved accurate detection. In addition, we explore the importance of explainable AI inside quantum models to enhance the interpretability of complex decision making process. By integrating Explainable AI (XAI) with quantum models has significantly improve security mechanisms and build strong trust within stakeholders. Our research have highlights impact of Explainable Quantum Convolutional Neural Networks (QCNNs) by enforcing cyber security in distributed systems.