The Internet is the most complex machine humankind has ever built, and how to defense it from intrusions is even more complex. With the ever increasing of new intrusions, intrusion detection task rely on Artificial Intelligence more and more. Interpretability and transparency of the machine learning model is the foundation of trust in AI-driven intrusion detection results. Current interpretation Artificial Intelligence technologies in intrusion detection are heuristic, which is neither accurate nor sufficient. This paper proposed a rigorous interpretable Artificial Intelligence driven intrusion detection approach, based on artificial immune system. Details of rigorous interpretation calculation process for a decision tree model is presented. Prime implicant explanation for benign traffic flow are given in detail as rule for negative selection of the cyber immune system. Experiments are carried out in real-life traffic.
翻译:互联网是人类有史以来建造的最复杂的机器,如何保护它不受入侵则更为复杂。随着新入侵的不断增加,入侵探测任务越来越依赖人工智能。机器学习模型的可解释性和透明度是信任AI驱动入侵探测结果的基础。目前对入侵探测人工智能技术的解释是超常的,既不准确,也不足够。本文提议了一种严格解释的人工智能入侵探测方法,其基础是人工免疫系统。提供了决策树模型严格解释计算过程的细节。对无害交通流量的初级解释作为负面选择网络免疫系统的规则得到了详细解释。实验是在实际交通中进行的。