基于隐藏标签节点的跨网络认证方法仿真

针对当前跨网络认证相关研究成果存在安全性能较差的问题,提出基于隐藏标签节点的跨网络认证方法。筛选出网络范围内度数比较大的节点当作识别目标,加入待配准节点聚类社团信息,分类挖掘隐藏标签节点,并将隶属同一类别的社团标签节点添加至待配准节点自中心网络范围,根据标签节点找到最优配准结果,通过迭代思想持续更新标签节点集合,直到不再有新标签节点出现,从而实现网络中全部节点身份识别;基于身份识别下的节点归类初步认证,结合信任度理念,实现跨网络的进一步认证,获取认证双方的信任度,构建网络之间信任关系,并同意访问本网络的数据资源,完成跨网络认证。实验结果表明,所提方法可有效检测出跨网络认证中的恶意访问,安全性能优于当前成果。

Simulation of Cross-Network Authentication Method Based on Hidden Tag Node

A cross-network authentication method based on hidden tag nodes was presented.First of all,the nodes whose degrees were relatively large within the network range were screened as the identification targets.After that,the cluster community information of the node to be registered was added,and the hidden label nodes were mined and classified.Moreover,the community tag nodes which belonged to the same category were added to the self-center network range of the node to be registered.According to the label node,the optimal registration result was found.In addition,the set of tag nodes was continuously updated through the iterative idea until there were no more new nodes,so that the identification of all the nodes in network was achieved.Based on the initial authentication of node classification under identity recognition,combined with the concept of credibility,the further authentication across the network was achieved to obtain the trust between the two parties.Finally,the trust relationship between the networks was constructed and the data resources accessing the network were agreed to finish the cross-network au-thentication.Simulation results prove that the proposed method can effectively detect malicious access in cross-net-work authentication.Meanwhile,the security performance is better than that of current results.