構建了基于免疫算法和神經網絡的新型抗體網絡入侵檢測系統，系統與網絡入侵檢測功能相結合，應用于大型網絡的入侵檢測任務，具有良好的可擴充性；重點討論了新型抗體網絡原理，引進BP神經網絡自學習能力，對已有的抗體網絡模型進行改進；通過對網絡數據集的測試表明，該算法相對于傳統抗體網絡，其檢測效率得到了明顯的改善。This paper designs an antibody network base on immune algorithm and neural network used for Intrusion Detection System. The Abnet network system combines network-based intrusion detection functions. It can be used to protect large area network and has relatively good expansibility. This paper also discusses the theory of the Abnet. How to implement of the Abnet with BP neural network in intrusion detection. Because of the traditional Abnet weakness in learning time and performance, This network is designed. The algorithm has been tested on a network data set. The result showed that it had much better performance than traditional Abnet.