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云服务器分布式数据端到端加密传输算法仿真

Simulation of End-to-End Encryption Transmission Algorithm for Distributed Data in Cloud Server
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摘要 个人隐私信息保护具有重要的研究意义,但传统蜜罐加密算法在抵御网络攻击上效率较低且稳定性较差。为解决上述问题,本文采用聚类算法优化DTE二次加密过程,大幅度减少了加、解码时间,提高了蜜罐算法的效率,通过与CTCDF网络结构有机融合,构建出KDC网络信息加密通信模型。模型首先基于k-modes聚类算法对优化数据进行分流处理;然后将分流失败的数据投入蜜罐算法中进行加密,以提升信息数据的安全性;接着利用优化调度制度的CTCDF构架对加密信息进行传输;最终采用加盐反运算与反向采样的方法,将加密信息进行明文解码。各基线模型仿真结果显示,在NKD和CID入侵检测数据上,KDC算法数据传输安全性平均提高了22.5%;且采用CTCDF网络后,较其它模型相比,KDC模型的加、解码时间降低了8.773%,内存资源占用量减少了1.245%,即KDC模型的效率更高。综上,KDC算法在CTCDF网络上减少了资源占用量与运算时间,且大幅度提高了数据的安全性,具有重要的仿真研究意义。 The protection of personal privacy information has important research significance,but the traditional honeypot encryption algorithm has low transmission efficiency and poor stability in resisting network attacks.In order to solve the above problems,this paper uses a clustering algorithm to optimize the second encryption process of DTE,which greatly reduces the time of adding and decoding,improves the efficiency of the honeypot algorithm,and integrates with the CTCDF network structure organically.The KDC network information encryption communication model is constructed.Firstly,the optimized data is shunted based on the k-modes clustering algorithm,and then the shunted failed data is put into the honeypot algorithm for encryption to improve the security of information data,and then the encrypted information is transmitted by using the CTCDF framework of the optimized scheduling system.Finally,the encrypted information is decoded by using the method of salt reverse operation and reverse sampling.The simulation results of each encryption transmission model show that the KDC algorithm improves the security of data transmission by 22.5%on average on NKD and CID intrusion detection data.Compared with other models,the adding and decoding time of the KDC model is reduced by 8.773%,and the amount of memory resources is reduced by 1.245%,that is,the KDC model is more efficient.To sum up,the KDC algorithm reduces the resource consumption and computing time on the CTCDF network,and greatly improves the data security,which has important research significance in simulation.
作者 郝聪妙 孟晓丽 王辉 HAO Cong-miao;MENG Xiao-li;WANG Hui(School of Computing,Zhengzhou Institute of Industrial Application Technology,Zhengzhou Henan 450000,China;Engineering College,Xi'an International University,Xi'an Shaanxi 710077,China;School of Computer Science and Engineering,Xi'an Technological University,Xi'an Shaanxi 710021,China)
出处 《计算机仿真》 2024年第10期317-322,共6页 Computer Simulation
基金 教育部产学合作协同育人项目(221005812103741)。
关键词 聚类算法优化 蜜罐加密算法 分布式数据 Clustering algorithm optimization Honeypot encryption algorithm Distributed data
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