基于信任量化的自治系统恶意性判定

Decision for Autonomous System Maliciousness Based on Quantitative Trust Measurement

鉴于当前域间路由系统未能有效解决自治系统节点的行为恶意性判定问题,论文在研究人际网络信任关系的基础上,提出一种基于信任量化的自治系统恶意性判定模型。模型通过定义直接判定、协作判定及配合度3项判定准则,综合分析及量化目标自治域的路由交互行为,同时定义节点参与度作为最终判定结果的放大因子。基于仿真路由拓扑进行验证,结果表明,在面对典型的路由欺骗、服务受限及协作节点误报的情况下,该模型均能够有效识别和判定目标自治域节点的恶意行为,具备较好准确性和稳定性。

Decision for Autonomous System maliciousness has not been effectively resolved within the current inter-domain routing system.On the basis of the research on trust relationship via the human society networks,a model of decision for the Autonomous System maliciousness based on the quantitative trust measurement is proposed.Three criteria including direct decision,collaborative decision and degree of coordination are defined,on which the comprehensive analysis and quantization towards the interactive routing behaviors of target Autonomous System,and the degree of participation is also defined as the amplifying factor.Experiments based on simulation topology is launched and the result indicates that,under the typical circumstances of routes spoofing,services restriction and intended incorrect decision by collaborative Autonomous System,the model can effectively discriminate and make reasonable decisions to the target malicious behavior,with good accuracy and stability.