基于多选项二次联合背包的态势感知资源分配算法

孙岩炜; 郭云川; 张玲翠; 方滨兴

doi:10.11959/j.issn.1000-436x.2016272

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基于多选项二次联合背包的态势感知资源分配算法

学术论文 | 更新时间：2024-06-05

- 基于多选项二次联合背包的态势感知资源分配算法
- Resource allocation algorithm for situation awareness based on multiple-choice quadratic knapsack
- 通信学报 2016年37卷第12期页码：56-66
- 作者机构：
  
  1. 中国科学院信息工程研究所信息安全国家重点实验室，北京 100093
  2. 东莞电子科技大学电子信息工程研究院，广东东莞 523808
- 作者简介：
  
  [ "孙岩炜（1989-），男，山西太原人，中国科学院信息工程研究所博士生，主要研究方向为网络安全。" ]
  [ "郭云川（1977-），男，四川营山人，博士，中国科学院信息工程研究所副研究员，主要研究方向为网络与信息系统安全、访问控制。" ]
  [ "张玲翠（1986-），女，河北故城人，中国科学院信息工程研究所博士生，主要研究方向为网络安全、信息保护。" ]
  [ "方滨兴（1960-），男，江西万年人，中国工程院院士，东莞电子科技大学教授，主要研究方向为计算机体系结构、计算机网络与信息安全。" ]
- 基金信息：
  
  中国科学院战略性科技先导专项基金资助项目(XDA06030200);国家重点研发计划基金资助项目(2016YFB0800303);国家重点研发计划基金资助项目(2016YFB0800700);国家“核高基”基金资助项目(2015ZX01029101);广东省产学研合作基金资助项目(2016B090921001)
- DOI：10.11959/j.issn.1000-436x.2016272
  中图分类号： TP301
- 网络首发：2016-12，
  
  纸质出版：2016-12-25
- 稿件说明：
移动端阅览
孙岩炜, 郭云川, 张玲翠, 等. 基于多选项二次联合背包的态势感知资源分配算法[J]. 通信学报, 2016,37(12):56-66.

Yan-wei SUN, Yun-chuan GUO, Ling-cui ZHANG, et al. Resource allocation algorithm for situation awareness based on multiple-choice quadratic knapsack[J]. Journal on Communications, 2016, 37(12): 56-66.
孙岩炜, 郭云川, 张玲翠, 等. 基于多选项二次联合背包的态势感知资源分配算法[J]. 通信学报, 2016,37(12):56-66. DOI： 10.11959/j.issn.1000-436x.2016272.

Yan-wei SUN, Yun-chuan GUO, Ling-cui ZHANG, et al. Resource allocation algorithm for situation awareness based on multiple-choice quadratic knapsack[J]. Journal on Communications, 2016, 37(12): 56-66. DOI： 10.11959/j.issn.1000-436x.2016272.

摘要

为了有效应对潜在网络威胁，通过合理利用资源达到最大化提升当前环境安全态势的目的，研究了有限资源的最优分配方案。网络态势的整体性特点使针对某一指标的改善可能会间接影响其他指标，并且投入力度不同，影响程度也有所差异。针对上述特性，将问题抽象成多选项二次联合背包模型，通过二次背包特性表示态势评估指标项之间的相互影响，通过多选项背包特性来表示单个指标项的多种投入可能。最后对其做半定规划松弛，采用分支定界法对问题进行求解。实验证明了算法的准确性和高效性。

Abstract

In order to deal with the potential cyber-threat and improve the security situation by using limited resource properly

the optimal allocation of resource focused on cyber security situation. The coherence of network situation lead to the fact that the enhancement of certain item may also affect some other items

and different amount of investment may also result in different degree of impact

therefore

the problem was extracted into the multiple-choice quadratic knapsack problem. The characteristics of quadratic knapsack problem was used to model the interactions among the situation indi-cator items

meanwhile used the multiple choice knapsack problem to model the multiple investment choice for each item. A branch and bound algorithm was conducted by using the semi-definite relaxation. The experiment results show the ac-curacy and efficiency of proposed algorithm.

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Keywords

references

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