With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive o...With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.展开更多
The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In t...The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.展开更多
Resilience of air&space defense system of systems(SoSs)is critical to national air defense security.However,the research on it is still scarce.In this study,the resilience of air&space defense SoSs is firstly ...Resilience of air&space defense system of systems(SoSs)is critical to national air defense security.However,the research on it is still scarce.In this study,the resilience of air&space defense SoSs is firstly defined and the kill network theory is established by combining super network and kill chain theory.Two cases of the SoSs are considered:(a)The kill chains are relatively homogenous;(b)The kill chains are relatively heterogenous.Meanwhile,two capability assessment methods,which are based on the number of kill chains and improved self-information quantity,respectively,are proposed.The improved self-information quantity modeled based on nodes and edges can achieve qualitative and quantitative assessment of the combat capability by using linguistic Pythagorean fuzzy sets.Then,a resilient evaluation index consisting of risk response,survivability,and quick recovery is proposed accordingly.Finally,network models for regional air defense and anti-missile SoSs are established respectively,and the resilience measurement results are verified and analyzed under different attack and recovery strategies,and the optimization strategies are also proposed.The proposed theory and method can meet different demands to evaluate combat capability and optimize resilience of various types of air&space defense and similar SoSs.展开更多
Through caching popular contents at the network edge,wireless edge caching can greatly reduce both the content request latency at mobile devices and the traffic burden at the core network.However,popularity-based cach...Through caching popular contents at the network edge,wireless edge caching can greatly reduce both the content request latency at mobile devices and the traffic burden at the core network.However,popularity-based caching strategies are vulnerable to Cache Pollution Attacks(CPAs)due to the weak security protection at both edge nodes and mobile devices.In CPAs,through initiating a large number of requests for unpopular contents,malicious users can pollute the edge caching space and degrade the caching efficiency.This paper firstly integrates the dynamic nature of content request and mobile devices into the edge caching framework,and introduces an eavesdroppingbased CPA strategy.Then,an edge caching mechanism,which contains a Request Pattern Change-based Cache Pollution Detection(RPC2PD)algorithm and an Attack-aware Cache Defense(ACD)algorithm,is proposed to defend against CPAs.Simulation results show that the proposed mechanism could effectively suppress the effects of CPAs on the caching performance and improve the cache hit ratio.展开更多
On March 5,the Ministry of Finance released the 2023 government budget draft report,according to which China’s defense budget of 2023 will be 1.55 trillion yuan(US$224.79 billion),an increase of 7.2 percent year on y...On March 5,the Ministry of Finance released the 2023 government budget draft report,according to which China’s defense budget of 2023 will be 1.55 trillion yuan(US$224.79 billion),an increase of 7.2 percent year on year,which is only 0.1 percentage points higher than 2022.The release of the defense budget attracted the attention of many foreign media outlets,some of which delivered distorted interpretations and exaggerated“China’s threat of force.”On March 6,Tan Kefei,spokesperson for the delegation of the People’s Liberation Army and the People’s Armed Police Force to the First Session of the 14th National People’s Congress,said that China has adhered to the principle of coordinated development of national defense and economic development.展开更多
In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems (OAADS) is hardly described in quantity with previous modeling approaches, a supernetwork model...In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems (OAADS) is hardly described in quantity with previous modeling approaches, a supernetwork modeling approach for the OAADS is put for- ward by extending granular computing. Based on that operational units and links are equal to different information granularities, the supernetwork framework of the OAADS is constructed as a “four- network within two-layer” structure by forming dynamic operating coalitions, and measuring indexes of the ripple-effect analysis for the OAADS are given combining with Laplace spectral radius. In this framework, via analyzing multidimensional attributes which inherit relations between operational units in different granular scales, an extended granular computing is put forward integrating with a topological structure. Then the operation process within the supernetwork framework, including transformation relations be- tween two layers in the vertical view and mapping relations among functional networks in the horizontal view, is studied in quantity. As the application case shows, comparing with previous modeling approaches, the supernetwork model can validate and analyze the operation mechanism in the air defense architecture, and the ripple-effect analysis can be used to confirm the key operational unit with micro and macro viewpoints.展开更多
Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as dev...Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.展开更多
In order to cope with the increasing threat of the ballistic missile(BM)in a shorter reaction time,the shooting policy of the layered defense system needs to be optimized.The main decisionmaking problem of shooting op...In order to cope with the increasing threat of the ballistic missile(BM)in a shorter reaction time,the shooting policy of the layered defense system needs to be optimized.The main decisionmaking problem of shooting optimization is how to choose the next BM which needs to be shot according to the previous engagements and results,thus maximizing the expected return of BMs killed or minimizing the cost of BMs penetration.Motivated by this,this study aims to determine an optimal shooting policy for a two-layer missile defense(TLMD)system.This paper considers a scenario in which the TLMD system wishes to shoot at a collection of BMs one at a time,and to maximize the return obtained from BMs killed before the system demise.To provide a policy analysis tool,this paper develops a general model for shooting decision-making,the shooting engagements can be described as a discounted reward Markov decision process.The index shooting policy is a strategy that can effectively balance the shooting returns and the risk that the defense mission fails,and the goal is to maximize the return obtained from BMs killed before the system demise.The numerical results show that the index policy is better than a range of competitors,especially the mean returns and the mean killing BM number.展开更多
Various application domains require the integration of distributed real-time or near-real-time systems with non-real-time systems.Smart cities,smart homes,ambient intelligent systems,or network-centric defense systems...Various application domains require the integration of distributed real-time or near-real-time systems with non-real-time systems.Smart cities,smart homes,ambient intelligent systems,or network-centric defense systems are among these application domains.Data Distribution Service(DDS)is a communication mechanism based on Data-Centric Publish-Subscribe(DCPS)model.It is used for distributed systems with real-time operational constraints.Java Message Service(JMS)is a messaging standard for enterprise systems using Service Oriented Architecture(SOA)for non-real-time operations.JMS allows Java programs to exchange messages in a loosely coupled fashion.JMS also supports sending and receiving messages using a messaging queue and a publish-subscribe interface.In this article,we propose an architecture enabling the automated integration of distributed real-time and non-real-time systems.We test our proposed architecture using a distributed Command,Control,Communications,Computers,and Intelligence(C4I)system.The system has DDS-based real-time Combat Management System components deployed to naval warships,and SOA-based non-real-time Command and Control components used at headquarters.The proposed solution enables the exchange of data between these two systems efficiently.We compare the proposed solution with a similar study.Our solution is superior in terms of automation support,ease of implementation,scalability,and performance.展开更多
One important mission of the strategic defense is to develop an integrated, layered ballistic missile defense system(BMDS). Considering the problem of assigning limited defense weapons to incoming ballistic missiles...One important mission of the strategic defense is to develop an integrated, layered ballistic missile defense system(BMDS). Considering the problem of assigning limited defense weapons to incoming ballistic missiles, we illustrate how defense weapons, ballistic missiles, kill probability and effectiveness of defense(ED) are interrelated and how to understand this relationship for achieving the best allocation plan. Motivated by the queueing theory, in which the available resources are not sufficient to satisfy the demands placed upon them at all times, the layered deployed defense weapon is modeled as a queueing system to shoot Poisson arrived targets. Simultaneously, examples, of optimum intercepts allocation problems under different constraints are presented. The four theorems determine the allocation rules of intercepts to targets that maximize ED or minimize the cost to achieve a required ED.展开更多
Based on the analysis of public expenditure performance,this article discusses the economy,efficiency,and effectiveness of defense expenditure performance,explains the relationship of the three,and emphasizes their un...Based on the analysis of public expenditure performance,this article discusses the economy,efficiency,and effectiveness of defense expenditure performance,explains the relationship of the three,and emphasizes their unity,interaction,and priority.The defense expenditure performance evaluation system,which is a comprehensive assessment of processes and results,is put forward along with the unification of economy,efficiency,and effectiveness.This system can be used to analyze whether the allocation and use of defense funds have achieved the strategic objectives of the Department of Defense.展开更多
For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carr...For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carry out for the dynamic evaluation on time series. In order to solve these problems, a threat evaluation method based on the AR(p)(auto regressive(AR))-dynamic improved technique for order preference by similarity to ideal solution(DITOPSIS) method is proposed. The AR(p) model is adopted to predict the missing data on the time series. Then, the entropy weight method is applied to solve each index weight at the objective point. Kullback-Leibler divergence(KLD) is used to improve the traditional TOPSIS, and to carry out the target threat evaluation. The Poisson distribution is used to assign the weight value.Simulation results show that the improved AR(p)-DITOPSIS threat evaluation method can synthetically take into account the target threat degree in time series and is more suitable for the threat evaluation under the condition of missing the target data than the traditional TOPSIS method.展开更多
The inherent selfishness of each node for the enhancement of message successful delivery ratio and the network overall performance improvement are reflected in the contradiction relationship of competition and coopera...The inherent selfishness of each node for the enhancement of message successful delivery ratio and the network overall performance improvement are reflected in the contradiction relationship of competition and cooperation in delay/disruption tolerant networks (DTN). In particular, the existence of malicious node aggravates this contradiction. To resolve this contradiction, social relationship theory and group theory of social psychology were adopted to do an in-depth analysis. The concrete balancing approach which leveraged Nash equilibrium theory of game theory was proposed to resolve this contradiction in reality. Thus, a new congestion control routing algorithm for security defense based on social psychology and game theory (CRSG) was put forward. Through the experiment, this algorithm proves that it can enhance the message successful delivery ratio by more than 15% and reduce the congestion ratio over 15% as well. This algorithm balances the contradiction relationship between the two key performance targets and made all nodes exhibit strong cooperation relationship in DTN.展开更多
The defense techniques for machine learning are critical yet challenging due tothe number and type of attacks for widely applied machine learning algorithms aresignificantly increasing. Among these attacks, the poison...The defense techniques for machine learning are critical yet challenging due tothe number and type of attacks for widely applied machine learning algorithms aresignificantly increasing. Among these attacks, the poisoning attack, which disturbsmachine learning algorithms by injecting poisoning samples, is an attack with the greatestthreat. In this paper, we focus on analyzing the characteristics of positioning samples andpropose a novel sample evaluation method to defend against the poisoning attack cateringfor the characteristics of poisoning samples. To capture the intrinsic data characteristicsfrom heterogeneous aspects, we first evaluate training data by multiple criteria, each ofwhich is reformulated from a spectral clustering. Then, we integrate the multipleevaluation scores generated by the multiple criteria through the proposed multiplespectral clustering aggregation (MSCA) method. Finally, we use the unified score as theindicator of poisoning attack samples. Experimental results on intrusion detection datasets show that MSCA significantly outperforms the K-means outlier detection in terms ofdata legality evaluation and poisoning attack detection.展开更多
Background:Since 2001,the French Armed Forces have sustained many casualties during the Global War on Terror;however,even today,there is no French Military trauma registry.Some French service members(SMs)were treated ...Background:Since 2001,the French Armed Forces have sustained many casualties during the Global War on Terror;however,even today,there is no French Military trauma registry.Some French service members(SMs)were treated in US Military Medical Treatment Facilities(MTFs)and were recorded in the US Department of Defense Trauma Registry(Do DTR).Our objective was to conduct a descriptive analysis of the injuries sustained by French SMs reported in the Do DTR and subsequent care provided to them to assist in understanding the importance of building a French Military trauma registry.Methods:Using Do DTR data collected from 2001 to 2017,a retrospective descriptive analysis was conducted.We identified 59 French SMs treated in US MTFs.The characteristics of the SMs’demographics,injuries,care provided to them,and discharge outcomes were summarized.Results:Among the 59 French SMs identified,46(78%)sustained battle injuries(BIs)and 13(22%)sustained nonbattle injuries(NBIs).There were 47(80%)SMs injured in Afghanistan(Opération Pamir),while 12(20%)were injured in Opération Chammal in Iraq and Syria.Explosives accounted for 52.5%of injuries,while 25.4%were due to gunshot wounds;all were BIs.The majority of reported injuries were penetrating(59.3%),most of which were BIs(71.7%).The mean Injury Severity Score for BIs was 12(SD=8.9)compared to 6(SD=1.7)for NBIs.Around half of SMs(n=30;51%)were injured in Afghanistan between the years 2008–2010.Among a total of 246 injuries sustained by 59 patients,extremities were the body part most prone to BIs followed by the head and face.Four SMs died after admission(6.8%).Conclusions:The Do DTR provides extensive data on trauma injuries that can be used to inform injury prevention and clinical care.The majority of injuries sustained by French SMs were BIs,caused by explosives,and predominantly occurring to the extremities;these findings are similar to those of other studies conducted in combat zones.There is a need to establish a French Military trauma registry to improve the combat casualty care provided to French SMs,and its creation may benefit from the Do DTR model.展开更多
Due to their advantages in flexibility,scalability,survivability,and cost-effectiveness,drone swarms have been increasingly used for reconnaissance tasks and have posed great challenges to their opponents on modern ba...Due to their advantages in flexibility,scalability,survivability,and cost-effectiveness,drone swarms have been increasingly used for reconnaissance tasks and have posed great challenges to their opponents on modern battlefields.This paper studies an optimization problem for deploying air defense systems against reconnaissance drone swarms.Given a set of available air defense systems,the problem determines the location of each air defense system in a predetermined region,such that the cost for enemy drones to pass through the region would be maximized.The cost is calculated based on a counterpart drone path planning problem.To solve this adversarial problem,we first propose an exact iterative search algorithm for small-size problem instances,and then propose an evolutionary framework that uses a specific encoding-decoding scheme for large-size problem instances.We implement the evolutionary framework with six popular evolutionary algorithms.Computational experiments on a set of different test instances validate the effectiveness of our approach for defending against reconnaissance drone swarms.展开更多
基金supported by the National Natural Science Foundation of China(71771216).
文摘With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.
基金National Natural Science Foundation of China(Grant No.62001506)to provide fund for conducting experiments。
文摘The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.
基金supported by National Natural Science Foundation of China,grant numbers 72001214National Social Science Foundation of China,Young Talent Fund of University Association for Science and Technology in Shaanxi,China,No.20190108Natural Science Foundation of Shaanxi Province,grant number 2020JQ-484.
文摘Resilience of air&space defense system of systems(SoSs)is critical to national air defense security.However,the research on it is still scarce.In this study,the resilience of air&space defense SoSs is firstly defined and the kill network theory is established by combining super network and kill chain theory.Two cases of the SoSs are considered:(a)The kill chains are relatively homogenous;(b)The kill chains are relatively heterogenous.Meanwhile,two capability assessment methods,which are based on the number of kill chains and improved self-information quantity,respectively,are proposed.The improved self-information quantity modeled based on nodes and edges can achieve qualitative and quantitative assessment of the combat capability by using linguistic Pythagorean fuzzy sets.Then,a resilient evaluation index consisting of risk response,survivability,and quick recovery is proposed accordingly.Finally,network models for regional air defense and anti-missile SoSs are established respectively,and the resilience measurement results are verified and analyzed under different attack and recovery strategies,and the optimization strategies are also proposed.The proposed theory and method can meet different demands to evaluate combat capability and optimize resilience of various types of air&space defense and similar SoSs.
文摘Through caching popular contents at the network edge,wireless edge caching can greatly reduce both the content request latency at mobile devices and the traffic burden at the core network.However,popularity-based caching strategies are vulnerable to Cache Pollution Attacks(CPAs)due to the weak security protection at both edge nodes and mobile devices.In CPAs,through initiating a large number of requests for unpopular contents,malicious users can pollute the edge caching space and degrade the caching efficiency.This paper firstly integrates the dynamic nature of content request and mobile devices into the edge caching framework,and introduces an eavesdroppingbased CPA strategy.Then,an edge caching mechanism,which contains a Request Pattern Change-based Cache Pollution Detection(RPC2PD)algorithm and an Attack-aware Cache Defense(ACD)algorithm,is proposed to defend against CPAs.Simulation results show that the proposed mechanism could effectively suppress the effects of CPAs on the caching performance and improve the cache hit ratio.
文摘On March 5,the Ministry of Finance released the 2023 government budget draft report,according to which China’s defense budget of 2023 will be 1.55 trillion yuan(US$224.79 billion),an increase of 7.2 percent year on year,which is only 0.1 percentage points higher than 2022.The release of the defense budget attracted the attention of many foreign media outlets,some of which delivered distorted interpretations and exaggerated“China’s threat of force.”On March 6,Tan Kefei,spokesperson for the delegation of the People’s Liberation Army and the People’s Armed Police Force to the First Session of the 14th National People’s Congress,said that China has adhered to the principle of coordinated development of national defense and economic development.
基金supported by the National Natural Science Foundation of China(61272011)
文摘In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems (OAADS) is hardly described in quantity with previous modeling approaches, a supernetwork modeling approach for the OAADS is put for- ward by extending granular computing. Based on that operational units and links are equal to different information granularities, the supernetwork framework of the OAADS is constructed as a “four- network within two-layer” structure by forming dynamic operating coalitions, and measuring indexes of the ripple-effect analysis for the OAADS are given combining with Laplace spectral radius. In this framework, via analyzing multidimensional attributes which inherit relations between operational units in different granular scales, an extended granular computing is put forward integrating with a topological structure. Then the operation process within the supernetwork framework, including transformation relations be- tween two layers in the vertical view and mapping relations among functional networks in the horizontal view, is studied in quantity. As the application case shows, comparing with previous modeling approaches, the supernetwork model can validate and analyze the operation mechanism in the air defense architecture, and the ripple-effect analysis can be used to confirm the key operational unit with micro and macro viewpoints.
文摘Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.
基金supported by the National Natural Science Foundation of China(7170120971771216)+1 种基金Shaanxi Natural Science Foundation(2019JQ-250)China Post-doctoral Fund(2019M653962)
文摘In order to cope with the increasing threat of the ballistic missile(BM)in a shorter reaction time,the shooting policy of the layered defense system needs to be optimized.The main decisionmaking problem of shooting optimization is how to choose the next BM which needs to be shot according to the previous engagements and results,thus maximizing the expected return of BMs killed or minimizing the cost of BMs penetration.Motivated by this,this study aims to determine an optimal shooting policy for a two-layer missile defense(TLMD)system.This paper considers a scenario in which the TLMD system wishes to shoot at a collection of BMs one at a time,and to maximize the return obtained from BMs killed before the system demise.To provide a policy analysis tool,this paper develops a general model for shooting decision-making,the shooting engagements can be described as a discounted reward Markov decision process.The index shooting policy is a strategy that can effectively balance the shooting returns and the risk that the defense mission fails,and the goal is to maximize the return obtained from BMs killed before the system demise.The numerical results show that the index policy is better than a range of competitors,especially the mean returns and the mean killing BM number.
文摘Various application domains require the integration of distributed real-time or near-real-time systems with non-real-time systems.Smart cities,smart homes,ambient intelligent systems,or network-centric defense systems are among these application domains.Data Distribution Service(DDS)is a communication mechanism based on Data-Centric Publish-Subscribe(DCPS)model.It is used for distributed systems with real-time operational constraints.Java Message Service(JMS)is a messaging standard for enterprise systems using Service Oriented Architecture(SOA)for non-real-time operations.JMS allows Java programs to exchange messages in a loosely coupled fashion.JMS also supports sending and receiving messages using a messaging queue and a publish-subscribe interface.In this article,we propose an architecture enabling the automated integration of distributed real-time and non-real-time systems.We test our proposed architecture using a distributed Command,Control,Communications,Computers,and Intelligence(C4I)system.The system has DDS-based real-time Combat Management System components deployed to naval warships,and SOA-based non-real-time Command and Control components used at headquarters.The proposed solution enables the exchange of data between these two systems efficiently.We compare the proposed solution with a similar study.Our solution is superior in terms of automation support,ease of implementation,scalability,and performance.
基金supported by the Military Graduate Student Foundation of Army
文摘One important mission of the strategic defense is to develop an integrated, layered ballistic missile defense system(BMDS). Considering the problem of assigning limited defense weapons to incoming ballistic missiles, we illustrate how defense weapons, ballistic missiles, kill probability and effectiveness of defense(ED) are interrelated and how to understand this relationship for achieving the best allocation plan. Motivated by the queueing theory, in which the available resources are not sufficient to satisfy the demands placed upon them at all times, the layered deployed defense weapon is modeled as a queueing system to shoot Poisson arrived targets. Simultaneously, examples, of optimum intercepts allocation problems under different constraints are presented. The four theorems determine the allocation rules of intercepts to targets that maximize ED or minimize the cost to achieve a required ED.
文摘Based on the analysis of public expenditure performance,this article discusses the economy,efficiency,and effectiveness of defense expenditure performance,explains the relationship of the three,and emphasizes their unity,interaction,and priority.The defense expenditure performance evaluation system,which is a comprehensive assessment of processes and results,is put forward along with the unification of economy,efficiency,and effectiveness.This system can be used to analyze whether the allocation and use of defense funds have achieved the strategic objectives of the Department of Defense.
基金supported by the Postdoctoral Science Foundation of China(2013T60923)
文摘For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carry out for the dynamic evaluation on time series. In order to solve these problems, a threat evaluation method based on the AR(p)(auto regressive(AR))-dynamic improved technique for order preference by similarity to ideal solution(DITOPSIS) method is proposed. The AR(p) model is adopted to predict the missing data on the time series. Then, the entropy weight method is applied to solve each index weight at the objective point. Kullback-Leibler divergence(KLD) is used to improve the traditional TOPSIS, and to carry out the target threat evaluation. The Poisson distribution is used to assign the weight value.Simulation results show that the improved AR(p)-DITOPSIS threat evaluation method can synthetically take into account the target threat degree in time series and is more suitable for the threat evaluation under the condition of missing the target data than the traditional TOPSIS method.
基金Projects(61202488, 61070199, 61103182) supported by the National Natural Science Foundation of China
文摘The inherent selfishness of each node for the enhancement of message successful delivery ratio and the network overall performance improvement are reflected in the contradiction relationship of competition and cooperation in delay/disruption tolerant networks (DTN). In particular, the existence of malicious node aggravates this contradiction. To resolve this contradiction, social relationship theory and group theory of social psychology were adopted to do an in-depth analysis. The concrete balancing approach which leveraged Nash equilibrium theory of game theory was proposed to resolve this contradiction in reality. Thus, a new congestion control routing algorithm for security defense based on social psychology and game theory (CRSG) was put forward. Through the experiment, this algorithm proves that it can enhance the message successful delivery ratio by more than 15% and reduce the congestion ratio over 15% as well. This algorithm balances the contradiction relationship between the two key performance targets and made all nodes exhibit strong cooperation relationship in DTN.
文摘The defense techniques for machine learning are critical yet challenging due tothe number and type of attacks for widely applied machine learning algorithms aresignificantly increasing. Among these attacks, the poisoning attack, which disturbsmachine learning algorithms by injecting poisoning samples, is an attack with the greatestthreat. In this paper, we focus on analyzing the characteristics of positioning samples andpropose a novel sample evaluation method to defend against the poisoning attack cateringfor the characteristics of poisoning samples. To capture the intrinsic data characteristicsfrom heterogeneous aspects, we first evaluate training data by multiple criteria, each ofwhich is reformulated from a spectral clustering. Then, we integrate the multipleevaluation scores generated by the multiple criteria through the proposed multiplespectral clustering aggregation (MSCA) method. Finally, we use the unified score as theindicator of poisoning attack samples. Experimental results on intrusion detection datasets show that MSCA significantly outperforms the K-means outlier detection in terms ofdata legality evaluation and poisoning attack detection.
文摘Background:Since 2001,the French Armed Forces have sustained many casualties during the Global War on Terror;however,even today,there is no French Military trauma registry.Some French service members(SMs)were treated in US Military Medical Treatment Facilities(MTFs)and were recorded in the US Department of Defense Trauma Registry(Do DTR).Our objective was to conduct a descriptive analysis of the injuries sustained by French SMs reported in the Do DTR and subsequent care provided to them to assist in understanding the importance of building a French Military trauma registry.Methods:Using Do DTR data collected from 2001 to 2017,a retrospective descriptive analysis was conducted.We identified 59 French SMs treated in US MTFs.The characteristics of the SMs’demographics,injuries,care provided to them,and discharge outcomes were summarized.Results:Among the 59 French SMs identified,46(78%)sustained battle injuries(BIs)and 13(22%)sustained nonbattle injuries(NBIs).There were 47(80%)SMs injured in Afghanistan(Opération Pamir),while 12(20%)were injured in Opération Chammal in Iraq and Syria.Explosives accounted for 52.5%of injuries,while 25.4%were due to gunshot wounds;all were BIs.The majority of reported injuries were penetrating(59.3%),most of which were BIs(71.7%).The mean Injury Severity Score for BIs was 12(SD=8.9)compared to 6(SD=1.7)for NBIs.Around half of SMs(n=30;51%)were injured in Afghanistan between the years 2008–2010.Among a total of 246 injuries sustained by 59 patients,extremities were the body part most prone to BIs followed by the head and face.Four SMs died after admission(6.8%).Conclusions:The Do DTR provides extensive data on trauma injuries that can be used to inform injury prevention and clinical care.The majority of injuries sustained by French SMs were BIs,caused by explosives,and predominantly occurring to the extremities;these findings are similar to those of other studies conducted in combat zones.There is a need to establish a French Military trauma registry to improve the combat casualty care provided to French SMs,and its creation may benefit from the Do DTR model.
基金supported by the National Natural Science Foundation of China(No.61872123)the Natural Science Foundation of Zhejiang Province(No.LR20F030002).
文摘Due to their advantages in flexibility,scalability,survivability,and cost-effectiveness,drone swarms have been increasingly used for reconnaissance tasks and have posed great challenges to their opponents on modern battlefields.This paper studies an optimization problem for deploying air defense systems against reconnaissance drone swarms.Given a set of available air defense systems,the problem determines the location of each air defense system in a predetermined region,such that the cost for enemy drones to pass through the region would be maximized.The cost is calculated based on a counterpart drone path planning problem.To solve this adversarial problem,we first propose an exact iterative search algorithm for small-size problem instances,and then propose an evolutionary framework that uses a specific encoding-decoding scheme for large-size problem instances.We implement the evolutionary framework with six popular evolutionary algorithms.Computational experiments on a set of different test instances validate the effectiveness of our approach for defending against reconnaissance drone swarms.