基于帕累托优化的网络安全设备部署设计与研究

Design and research of cyber security device deployment based on Pareto optimality

通过部署网络安全设备可以有效地提高网络的安全性,但由于网络设备种类繁多、功能复杂,如何在整个网络中最优地部署网络安全设备,从而达到安全和开销的平衡,仍是研究人员关注的焦点。将网络安全设备最优部署问题转换为帕累托优化问题,提出分布式约束优化的七元组对网络安全设备部署进行量化赋值,构建基于分支界限算法的部署方案搜索算法,在解空间内对量化的数值进行计算并求出最优解。由于基于分支界限算法的方案搜索算法需要耗费大量时间,在大型网络中运行效率较低,使用基于弧一致优化的数据预处理技术对量化数值进行预处理,实现搜索算法的优化。最后通过仿真实验测试,证明该方法的正确性和有效性。

By deploying cyber security devices,cyber security can be effectively improved. But due to the varieties and complex function of cyber equipment,how to optimize the deployment of cyber security devices is still a core problem for researchers. By turning the deployment of cyber security equipment into a Pareto optimization problem,this paper put forward a tuple,a distributed constraint optimization,to quantify the deployment of cyber security device. Then,based on branch and bound algorithm,it used the algorithm to calculate the quantized values to find out the optimal solution within solution space.And it took a lot of time to run the algorithm,based on branch and bound algorithm,which was infeasible in large networks.This paper proposed to use the data preprocessing technology to optimize the search,which was based on arc consistency technology. This paper computed the quantized value in advance and made the search become an easy problem. Finally,it used the simulation experiments to prove the correctness and effectiveness of the proposed approaches.