Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain info...Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain information of the opponents.As such,this paper presents a cooperative decision-making method based on incomplete information dynamic game to generate maneuver strategies for multiple UAVs in air combat.Firstly,a cooperative situation assessment model is presented to measure the overall combat situation.Secondly,an incomplete information dynamic game model is proposed to model the dynamic process of air combat,and a dynamic Bayesian network is designed to infer the tactical intention of the opponent.Then a reinforcement learning framework based on multiagent deep deterministic policy gradient is established to obtain the perfect Bayes-Nash equilibrium solution of the air combat game model.Finally,a series of simulations are conducted to verify the effectiveness of the proposed method,and the simulation results show effective synergies and cooperative tactics.展开更多
工业互联网在大幅提升传统工业控制系统的协同能力和运行效率的同时,也带来了日益增长的网络安全问题,典型威胁有分布式拒绝服务(distributed denial of service,DDoS),重放攻击(replay attack,RA),虚假数据注入等。本文以DDoS和RA这两...工业互联网在大幅提升传统工业控制系统的协同能力和运行效率的同时,也带来了日益增长的网络安全问题,典型威胁有分布式拒绝服务(distributed denial of service,DDoS),重放攻击(replay attack,RA),虚假数据注入等。本文以DDoS和RA这两种典型威胁为例,研究了基于自动化蜜罐的工业互联网不完全信息攻防博弈问题。具体的,利用不完全信息静态博弈描述了信息不对称下攻防博弈双方的交互过程,建立了基于自动化蜜罐的不完全信息静态攻防博弈模型,并通过Harsanyi转换求解该模型的贝叶斯纳什均衡策略。同时,研究了蜜罐配置成本约束下自动化蜜罐最优防御策略选取方法。最后,仿真结果表明该模型能够有效提高工业互联网环境中部署的自动化蜜罐的防御能力。展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61933010 and 61903301)Shaanxi Aerospace Flight Vehicle Design Key Laboratory。
文摘Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain information of the opponents.As such,this paper presents a cooperative decision-making method based on incomplete information dynamic game to generate maneuver strategies for multiple UAVs in air combat.Firstly,a cooperative situation assessment model is presented to measure the overall combat situation.Secondly,an incomplete information dynamic game model is proposed to model the dynamic process of air combat,and a dynamic Bayesian network is designed to infer the tactical intention of the opponent.Then a reinforcement learning framework based on multiagent deep deterministic policy gradient is established to obtain the perfect Bayes-Nash equilibrium solution of the air combat game model.Finally,a series of simulations are conducted to verify the effectiveness of the proposed method,and the simulation results show effective synergies and cooperative tactics.
文摘工业互联网在大幅提升传统工业控制系统的协同能力和运行效率的同时,也带来了日益增长的网络安全问题,典型威胁有分布式拒绝服务(distributed denial of service,DDoS),重放攻击(replay attack,RA),虚假数据注入等。本文以DDoS和RA这两种典型威胁为例,研究了基于自动化蜜罐的工业互联网不完全信息攻防博弈问题。具体的,利用不完全信息静态博弈描述了信息不对称下攻防博弈双方的交互过程,建立了基于自动化蜜罐的不完全信息静态攻防博弈模型,并通过Harsanyi转换求解该模型的贝叶斯纳什均衡策略。同时,研究了蜜罐配置成本约束下自动化蜜罐最优防御策略选取方法。最后,仿真结果表明该模型能够有效提高工业互联网环境中部署的自动化蜜罐的防御能力。
