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依据人体免疫系统抗体浓度的变化与病原体入侵强度的对应关系,提出了一种基于免疫的网络安全风险检测模型(Insre),给出了网络环境下自体、非自体、抗体、抗原、免疫细胞等的表示方法,建立了自体演化、抗体基因库、自体耐受、克隆选择、成熟细胞的产生与淘汰机制、动态免疫记忆、免疫监视等的抽象数学模型及相应的递推方程,在此基础上建立了基于抗体浓度的网络安全风险检测的定量计算模型,并给出了其理论推导和证明.利用该模型,可以实时定量地计算出网络当前所面临攻击的类别、数量、强度及风险指标等.理论分析和实验结果表明该方法是网络安全风险在线检测一种有效的新途径.
According to the relationship between the change of antibody concentration of human immune system and the invasion intensity of pathogens, an immune-based network security risk detection model (Insre) is proposed, and the self-a non-self-antibodies, antibodies, antigens, immune cells and so on The abstract mathematical model and corresponding recursive equations of self-evolution, antibody gene pool, self-tolerance, clonal selection, generation and elimination mechanism of mature cells, dynamic immune memory, immune surveillance and so on were established The quantitative calculation model of network security risk detection based on antibody concentration is established and its theoretical deduction and proof are given.Using this model, the types, quantity, intensity and risk index of network attack can be calculated in real time and quantitatively The theoretical analysis and experimental results show that this method is an effective new approach for on - line detection of network security risks.