Complex Networks Immune Strategy Based on Acquaintance Immunization
基于熟人免疫的复杂网络免疫策略

We proposed one synthesis immunization algorithem aiming at the drawbacks of acquaintance and target immunization and improve them separately. This immunization strategy randomly chooses nodes in network and adoptes different action according to different characteristics. This trategy remains the advantage of acquaintance that is based on local information without global structure and high degree nodes. It is more effective in the situation that the number of node need to be immunized is the same as target immunization. The better effectivity and wider situation of application were verified throughout simulation on scale free, random and some real-world networks.