[1]朱 洁.基于人工神经网络的信息安全加密管理评估[J].计算机技术与发展,2019,29(09):97-101.[doi:10. 3969 / j. issn. 1673-629X. 2019. 09. 019]
　ZHU Jie.Evaluation of Information Security Encryption Management Based on Artificial Neural Network[J].,2019,29(09):97-101.[doi:10. 3969 / j. issn. 1673-629X. 2019. 09. 019]
点击复制

基于人工神经网络的信息安全加密管理评估()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年09期
页码:
97-101
栏目:
安全与防范
出版日期:
2019-09-10

文章信息/Info

Title:
Evaluation of Information Security Encryption Management Based on Artificial Neural Network
文章编号:
1673-629X(2019)09-0097-05
作者:
朱 洁
广东工业大学华立学院,广东 广州 511325
Author(s):
ZHU Jie
Huali College Guangdong University of Technology,Guangzhou 511325,China
关键词:
人工神经网络; 虚拟机; 信息安全管理; 信息加密
Keywords:
artificial neural network; virtual machine; information security management; information encryption
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 09. 019
摘要:
为了提高云数据中心虚拟机信息管理平台的信息安全管理能力,提出一种基于人工神经网络的虚拟机信息安全加密评估方法。 在全面分析云数据中心虚拟机信息管理平台建设安全事件的基础上,采用 Logistics 混沌映射进行数据加密的同态映射设计,基于人工神经网络理论构造云数据中心虚拟机信息管理平台的风险评估模型,对虚拟机云数据进行密钥授权。 根据链路层重加密钥检测结果进行信息安全加密的自适应编码设计,实现了虚拟机信息安全的量化评估。 在人工神经网络的隐含层采用自适应学习算法进行信息安全编码,依据收敛条件进行云数据中心虚拟机信息加密的过程管理,提高信息加密传输能力,实现信息安全评估。 仿真结果表明,采用该方法进行云数据中心虚拟机信息安全评估的准确性较好,防攻击能力较强,确保了信息安全。
Abstract:
In order to improve the ability of information security management of cloud data center virtual machine information management platform,a method of encrypting and evaluating virtual machine information security based on artificial neural network is proposed. On the basis of analyzing the security events of cloud data center virtual machine information management platform,Logistics chaotic mapping is used to design the homomorphic map of data encryption. Based on the theory of artificial neural network,the risk assessment model of cloud data center virtual machine information management platform is constructed,and the virtual machine cloud data is authorized by key. According to the result of link layer recombination key detection,the adaptive coding design of information security encryption is carried out,and the quantization evaluation of virtual machine information security is realized. In the hidden layer of artificial neural network,adaptive learning algorithm is used to encode information security. According to the convergence condition,the process of information encryption in cloud data center virtual machine is managed,the ability of information encryption and transmission is improved,and the information security evaluation is realized. The simulation shows that this method is more accurate and has strong anti-attack ability to evaluate the information security of virtual machine in cloud data center,which ensures the information security.

相似文献/References:

[1]周平东 陈榕.CAR构件的四种运行时形态[J].计算机技术与发展,2010,(04):1.
　ZHOU Ping-dong,CHEN Rong.Running States of CAR in Elaura[J].,2010,(09):1.
[2]周毅敏 陈榕.Dalvik虚拟机进程模型分析[J].计算机技术与发展,2010,(02):83.
　ZHOU Yi-min,CHEN Rong.Analysis about Process in Dalvik Virtual Machine[J].,2010,(09):83.
[3]黄永聪 张旭[] 吴义纯 吴琦 程家兴.改进的径向基函数网络的研究及应用[J].计算机技术与发展,2010,(05):158.
　HUANG Yong-cong,ZHANG Xu,WU Yi-chun,et al.Research and Application of Improved Genetic Algorithm-Based RBFANN[J].,2010,(09):158.
[4]包敬海 周小珠 樊东红.基于VMWare构建虚拟网络实验室的研究[J].计算机技术与发展,2010,(06):242.
　BAO Jing-hai,ZHOU Xiao-zhu,FAN Dong-hong.Research of Building Virtual Network Laboratory Based on VMWare[J].,2010,(09):242.
[5]戴芬 刘希玉 王晓敏.蚁群神经网络在中小企业信用评价中的应用[J].计算机技术与发展,2009,(10):218.
　DAI Fen,LIU Xi-yu,WANG Xiao-min.Application of Ant Colony Neural Network to Credit Evaluation of Small and Middle Enterprises[J].,2009,(09):218.
[6]陈丹伟 黄秀丽 任勋益.基于人工神经网络入侵检测模型的探讨[J].计算机技术与发展,2009,(12):143.
　CHEN Dan-wei,HUANG Xiu-li,REN Xun-yi.An Approach to IDS Model Based on Artificial Neuron Network[J].,2009,(09):143.
[7]孙昊 张琦 许勇[].机器学习在GDP预测分析中的应用研究[J].计算机技术与发展,2009,(02):227.
　SUN Hao,ZHANG Qi,XU Yong[].Study on Prediction and Analysis of GDP Based on Machine Learning[J].,2009,(09):227.
[8]黄一丹 严洪森 冯丽娟 吴奇.基于C#．NET与Matlab接口和BP网络的汽车产量预测[J].计算机技术与发展,2008,(11):36.
　HUANG Yi-dan,YAN Hong-sen,FENG Li-juan,et al.Vehicle Production Forecasting Based on BPNN and Interface Between C #. NET and Matlab[J].,2008,(09):36.
[9]王书宇 李龙澍 汪群山.改进的协同进化遗传算法在机器博弈中的应用[J].计算机技术与发展,2008,(12):4.
　WANG Shu-yu,LI Long-shu,WANG Qun-shan.Application of Co- evolution and PSO Algorithm in Machine Game[J].,2008,(09):4.
[10]王建雄 刘应龙.基于人工神经网络的数字识别系统的研究[J].计算机技术与发展,2006,(05):26.
　WANG Jian-xiong,LIU Ying-long.Digital Recognition System Based on Artificial Neural Network[J].,2006,(09):26.

更新日期/Last Update: 2019-09-10