网络与信息安全学报 ›› 2020, Vol. 6 ›› Issue (2): 96-105.doi: 10.11959/j.issn.2096-109x.2020003

• 学术论文 • 上一篇    下一篇

基于隔离等级的网络切片部署方法

潘启润,黄开枝,游伟   

  1. 战略支援部队信息工程大学,河南 郑州 450001
  • 修回日期:2019-06-06 出版日期:2020-04-15 发布日期:2020-04-23
  • 作者简介:潘启润(1993- ),女,河北石家庄人,战略支援部队信息工程大学硕士生,主要研究方向为新一代移动通信技术、网络切片|黄开枝(1973- ),女,安徽滁州人,战略支援部队信息工程大学教授、博士生导师,主要研究方向为移动通信、无线物理层安全|游伟(1984- ),男,江西丰城人,战略支援部队信息工程大学讲师,主要研究方向为密码学、5G网络安全
  • 基金资助:
    国家重点研发计划网络空间安全专项基金资助项目(2016YFB0801605);国家自然科学基金创新群体基金资助项目(61521003);国家自然科学基金资助项目(61801515)

Network slicing deployment method based on isolation level

Qirun PAN,Kaizhi HUANG,Wei YOU   

  1. Strategic Support Force Information Engineering University,Zhengzhou 450001,China
  • Revised:2019-06-06 Online:2020-04-15 Published:2020-04-23
  • Supported by:
    The National Key R&D Program Cyberspace Security Project(2016YFB0801605);The National Natural Science Foundation Innovation Group Project(61521003);The National Natural Science Foundation of China(61801515)

摘要:

为了兼顾网络切片的性能隔离需求和安全隔离需求,提出了一种基于隔离等级的网络切片部署方法。该方法首先从性能隔离和安全隔离两方面确定了网络切片实例的隔离等级,在选择合适的位置部署虚拟节点时,不但保证所有网络切片实例均能达到各自的性能水平和安全水平,而且从隔离等级差值入手对虚拟节点共存的条件进行限制;然后利用整数线性规划方法对该问题进行建模,把部署成本最小化作为目标函数;最后使用基于遗传算法改进的粒子群算法求出最终的部署结果。仿真结果表明,该方法具有较低的部署成本和较高的收益开销比,并且能够同时保证性能和安全两方面的需求。

关键词: 网络切片, 隔离, 性能下降, 侧信道攻击

Abstract:

In order to balance the performance isolation requirements and security isolation requirements of network slicing,a network slice deployment method based on isolation level was proposed.The method first determined the isolation level of the network slice instance from the aspects of performance isolation and security isolation.When deploying the virtual nodes in the appropriate location,not only ensured that all network slice instances could reach their respective performance levels and security levels,but also isolated them.The gradation difference started to limit the coexistence condition of the virtual node.Then the integer linear programming method was used to model the problem,and the deployment cost was minimized as the objective function.Finally,the particle swarm optimization algorithm based on genetic algorithm was used to find the final deployment result.The simulation results show that the method has lower deployment cost and higher benefit-to-cost ratio,and can guarantee both performance and security.

Key words: network slicing, isolation, performance degradation, side channel attack

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