As cyberattacks grow more advanced and privacy laws become stricter, security systems must be powerful, transparent, and privacy-friendly. This paper introduces SwarmFL-XAI, a new framework that blends nature-inspired intelligence, collaborative learning, and explainable AI to deliver secure, scalable, and trustworthy threat detection. By using an ant-based strategy for sharing and updating models across devices, the system handles uneven data and malicious behaviour while avoiding the risks of a central server. Tools like SHAP and LIME explain why decisions are made, giving analysts clear insights and greater confidence. Tests on the UNSW-NB15 and CICIDS2017 datasets show strong results, wi... More >