DoS攻击下基于CSA的改进Kalman滤波研究  

Research on Improved Kalman Filter Based on CSA under DoS Attacks

作　　者：李新 雷安炙 朱良宽[1] LI Xin;LEI An-zhi;ZHU Liang-kuan(College of Computer and Control Engineering,Northeast Forestry University,Heilongjiang Harbin 150040,China)

机构地区：[1]东北林业大学计算机与控制工程学院,黑龙江哈尔滨150040

出　　处：《计算机仿真》2024年第12期362-368,共7页Computer Simulation

基　　金：国家自然科学基金(31370710);中央高校基本科研业务费专项资金(2572022BF05,2572023CT15-05);黑龙江省博士后科学基金(LBH-Z22053);黑龙江省优秀青年基金项目(YQ2023F002);国家博士后基金第73批面上(2023M730528)。

摘　　要：信息物理系统(CPS)借助共享网络实时传输信息的过程容易遭受拒绝服务(DoS)攻击的影响。为此创新设计了一种基于变色龙群算法(CSA)的改进Kalman滤波器,增强Kalman滤波算法的DoS攻击检测能力,并进一步提高Kalman滤波算法的输出预测准确性。首先,对比三种不同检测指标下攻击检测效果,为保证Kalman滤波的有效性,设计状态更新补偿策略提高滤波性能。其次,引入CSA优化滤波器参数,确保未发生攻击时预测输出的准确跟随以及攻击发生时对状态更新过程的精准补偿。最后,在仿真中对比筛选出最优检测指标,验证所设计的Kalman滤波具有良好的攻击检测与输出预测效果。Cyber-physical systems(CPS)often rely on shared networks for real-time information transmission,making them vulnerable to network attacks,particularly Denial of Service(DoS)attacks,which are commonly encountered.In this study,an improved Kalman filter based on the chameleon swarm algorithm(CSA)is designed to enhance the ability of the Kalman filter algorithm to detect attacks and predict CPS outputs.Firstly,the effectiveness of attack detection is compared under three different detection indicators.In order to ensure the effectiveness of the Kalman filter,a state update compensation strategy is designed to improve the filtering performance.Secondly,the CSA is introduced to optimize the filter parameters,ensuring the accurate prediction of the output when no attack occurs and precise compensation of the state update process when attacks occur.Finally,the optimal detection indicator is selected in simulation experiments,and the designed Kalman filter is verified to feature good effectiveness in attack detection and output prediction.

关 键 词：信息物理系统 拒绝服务攻击 卡尔曼滤波器 变色龙群算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]