Intrusion Response Model Based on AIS

The proposed immune-based intrusion response model depending on the self-learning and diversity of an artificial immune system, can recognize unknown attacks and classify them. It eliminates the influence of redundant affairs and quantitatively describes the danger facing by the system with the antibody concentration. The quantitative calculations of response cost and benefit are demonstrated. A dynamic response decision-making mechanism is also established, which can dynamically adjust the defending strategies according to the changing environment and use the minimum cost to guarantee the safe of a system. The experiment proves that this model has some desirable features, such as self-adaptation, rationality, quantitative calculation, etc. This model provides an effective method for the new intrusion response system.