  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.
