In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies wh...The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.展开更多
This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained...This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained by combining trajectory calculation with kill probability calculation. Then, coordinates of a fire point relative to standard kill probability value in terms of standardization method are found. At last, equivalent kill probability curve equations are formulated by means of curve fitting method.展开更多
A new method called local accurate search is put forward to calculate the allowable area for air-to-surface missiles based on the conventional methods. Comparing with traditional methods, the local accurate search met...A new method called local accurate search is put forward to calculate the allowable area for air-to-surface missiles based on the conventional methods. Comparing with traditional methods, the local accurate search method can search the area online and reduce the time of search with the required precision. Combining the traditional flight range table with a model calculation method, the new method employs the local search to fred an accurate result, which will meet the fast-calculation requirements for attacking moving targets. In this way, the missiles are adapted for the complex warfare situation.展开更多
A definition of self-determined priority is used in airfight decision firstly. A scheme of grouping the whole fighters is introduced, and the principle of target assignment and fire control is designed. Based on the ...A definition of self-determined priority is used in airfight decision firstly. A scheme of grouping the whole fighters is introduced, and the principle of target assignment and fire control is designed. Based on the neutral network, the decision algorithm is derived and the whole coordinated decision system is simulated. Secondly an algorithm for missile-attacking area is described and its calculational result is obtained under initial conditions. Then the attacking of missile is realized by the proportion guidance. Finally, a multi-target attack system. The system includes airfight decision, estimation of missile attack area and calculation of missile attack procedure. A digital simulation demonstrates that the airfight decision algorithm is correct. The methods have important reference values for the study of fire control system of the fourth generation fighter.展开更多
Vehicular Ad-hoc Networks (VANETs) technology has recently emerged, and gaining significant attention from the research because it is promising technologies related to Intelligent Transportation System (ITSs) and smar...Vehicular Ad-hoc Networks (VANETs) technology has recently emerged, and gaining significant attention from the research because it is promising technologies related to Intelligent Transportation System (ITSs) and smart cities. Wireless vehicular communication is employed to improve traffic safety and to reduce traffic congestion. Each vehicle in the ad-hoc network achieves as a smart mobile node categorized by high mobility and forming of dynamic networks. As a result of the movement of vehicles in a continuous way, VANETs are vulnerable to many security threats so it requisites capable and secure communication. Unfortunately, Ad hoc networks are liable to varied attacks like Block Hole attacks and Grey Hole attacks, Denial of service attacks, etc. Among the most known attacks are the Black Hole attacks while the malicious vehicle is able to intercept the data and drops it without forwarding it to the cars. The main goal of our simulation is to analyze the performance impact of black hole attack in real time vehicular traffic in the Greater Detroit Area using NS-2 and SUMO (Simulation of Urban). The simulation will be with AODV protocol.展开更多
ARP-based Distributed Denial of Service (DDoS) attacks due to ARP-storms can happen in local area networks where many computer systems are infected by worms such as Code Red or by DDoS agents. In ARP attack, the DDoS ...ARP-based Distributed Denial of Service (DDoS) attacks due to ARP-storms can happen in local area networks where many computer systems are infected by worms such as Code Red or by DDoS agents. In ARP attack, the DDoS agents constantly send a barrage of ARP requests to the gateway, or to a victim computer within the same sub-network, and tie up the resource of attacked gateway or host. In this paper, we set to measure the impact of ARP-attack on resource exhaustion of computers in a local area network. Based on attack experiments, we measure the exhaustion of processing and memory resources of a victim computer and also other computers, which are located on the same network as the victim computer. Interestingly enough, it is observed that an ARP-attack not only exhausts resource of the victim computer but also significantly exhausts processing resource of other non-victim computers, which happen to be located on the same local area network as the victim computer.展开更多
Salt attack performance of magnesium oxychloride cement(MOC) in brine was investigated from the viewpoints of strength development and strength coefficient. Microstructure was studied using quantitative X-ray diffract...Salt attack performance of magnesium oxychloride cement(MOC) in brine was investigated from the viewpoints of strength development and strength coefficient. Microstructure was studied using quantitative X-ray diffraction(QXRD), thermogravimetry(TG) and scanning electron microscopy(SEM). The results show that MOC mortars have outstanding salt attack performance after aging brine and raw brine immersion. The salt attack coefficients of MOC mortars are higher than 0.8, which is qualified for application in saline soil and salt lake area. The reason is that salt brine solution enters into the voids of MOC and plays a role of toughening and strengthening in the MOC.展开更多
This paper aims at analyzing the security issues that lie in the application layer (AL) protocols when users connect to the Internet via a wireless local area network (WLAN) through an access point. When adversaries l...This paper aims at analyzing the security issues that lie in the application layer (AL) protocols when users connect to the Internet via a wireless local area network (WLAN) through an access point. When adversaries launch deauthentication flood attacks cutting users' connection, the connection managers will automatically research the last access point's extended service set identifier (ESSID) and then re-establish connection. However, such re-connection can lead the users to a fake access point with the same ESSID set by attackers. As the attackers hide behind users' access points, they can pass AL's authentication and security schemes, e.g. secure socket layer (SSL). We have proved that they can even spy on users' account details, passwords, data and privacy.展开更多
[目的]DDoS攻击作为一种破坏性极强的网络威胁,严重影响电力系统的稳定运行。由于电力监控局域网中的数据流量复杂多变,DDoS攻击流量与正常流量在表现形式上存在较高相似性,导致二者难以有效区分。传统的静态阈值方法虽能在一定程度上...[目的]DDoS攻击作为一种破坏性极强的网络威胁,严重影响电力系统的稳定运行。由于电力监控局域网中的数据流量复杂多变,DDoS攻击流量与正常流量在表现形式上存在较高相似性,导致二者难以有效区分。传统的静态阈值方法虽能在一定程度上实现流量监测,但因无法适应流量的动态变化,常出现误判,从而削弱了对DDoS攻击的检测效果,难以为电力监控局域网提供可靠的安全保障。为此,提出一种基于动态阈值的电力监控局域网DDoS攻击检测方法。[方法]通过网络流量采集设备实时获取电力监控局域网的流量数据,并利用信息熵理论计算流量熵值。信息熵可反映数据的混乱程度:正常流量通常具有一定规律性,熵值相对稳定;而DDoS攻击流量因异常数据包的大量涌入,导致熵值显著波动。基于此特性,本文设定动态阈值,当流量熵值超过阈值时判定为异常流量。随后,提取异常流量的六元组特征集(包括平均流包数、平均字节数、源IP地址增速、流表生存时间变化、端口增速以及对流比),并将其输入预训练的最小二乘支持向量机(least squares support vector machine,LSSVM)分类器中。LSSVM通过对已知样本的学习建立特征与类别的映射关系,从而实现对异常流量的分类与判断,确定其是否为DDoS攻击流量。[结果]实验结果表明,本文方法在ROC曲线和PR曲线上均表现较好,ROC-AUC和PR-AUC值均较传统方法有所提高。这表明该方法在检测DDoS攻击时具备更高的准确率与召回率,能够有效识别隐藏于正常流量中的攻击流量,并显著降低误判率。[结论]基于动态阈值与LSSVM分类器的检测方法能够有效应对电力监控局域网中DDoS攻击与正常流量难以区分的问题,提升检测的准确性与可靠性,为电力监控局域网提供更为有效的DDoS攻击防护手段,有助于增强电力系统的安全性与稳定性,保障电力供应的可靠运行,对电力行业网络安全防护具有重要的实际应用价值。展开更多
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金supported by the Key Laboratory of Defense Science and Technology Foundation of Luoyang Electro-optical Equipment Research Institute(6142504200108)。
文摘The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.
文摘This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained by combining trajectory calculation with kill probability calculation. Then, coordinates of a fire point relative to standard kill probability value in terms of standardization method are found. At last, equivalent kill probability curve equations are formulated by means of curve fitting method.
文摘A new method called local accurate search is put forward to calculate the allowable area for air-to-surface missiles based on the conventional methods. Comparing with traditional methods, the local accurate search method can search the area online and reduce the time of search with the required precision. Combining the traditional flight range table with a model calculation method, the new method employs the local search to fred an accurate result, which will meet the fast-calculation requirements for attacking moving targets. In this way, the missiles are adapted for the complex warfare situation.
文摘A definition of self-determined priority is used in airfight decision firstly. A scheme of grouping the whole fighters is introduced, and the principle of target assignment and fire control is designed. Based on the neutral network, the decision algorithm is derived and the whole coordinated decision system is simulated. Secondly an algorithm for missile-attacking area is described and its calculational result is obtained under initial conditions. Then the attacking of missile is realized by the proportion guidance. Finally, a multi-target attack system. The system includes airfight decision, estimation of missile attack area and calculation of missile attack procedure. A digital simulation demonstrates that the airfight decision algorithm is correct. The methods have important reference values for the study of fire control system of the fourth generation fighter.
文摘Vehicular Ad-hoc Networks (VANETs) technology has recently emerged, and gaining significant attention from the research because it is promising technologies related to Intelligent Transportation System (ITSs) and smart cities. Wireless vehicular communication is employed to improve traffic safety and to reduce traffic congestion. Each vehicle in the ad-hoc network achieves as a smart mobile node categorized by high mobility and forming of dynamic networks. As a result of the movement of vehicles in a continuous way, VANETs are vulnerable to many security threats so it requisites capable and secure communication. Unfortunately, Ad hoc networks are liable to varied attacks like Block Hole attacks and Grey Hole attacks, Denial of service attacks, etc. Among the most known attacks are the Black Hole attacks while the malicious vehicle is able to intercept the data and drops it without forwarding it to the cars. The main goal of our simulation is to analyze the performance impact of black hole attack in real time vehicular traffic in the Greater Detroit Area using NS-2 and SUMO (Simulation of Urban). The simulation will be with AODV protocol.
文摘ARP-based Distributed Denial of Service (DDoS) attacks due to ARP-storms can happen in local area networks where many computer systems are infected by worms such as Code Red or by DDoS agents. In ARP attack, the DDoS agents constantly send a barrage of ARP requests to the gateway, or to a victim computer within the same sub-network, and tie up the resource of attacked gateway or host. In this paper, we set to measure the impact of ARP-attack on resource exhaustion of computers in a local area network. Based on attack experiments, we measure the exhaustion of processing and memory resources of a victim computer and also other computers, which are located on the same network as the victim computer. Interestingly enough, it is observed that an ARP-attack not only exhausts resource of the victim computer but also significantly exhausts processing resource of other non-victim computers, which happen to be located on the same local area network as the victim computer.
基金Funded by the Special Project Major Project for the Transformation of Scientific and Technological Achievements of Qinghai Province(Nos.2019-GX-165 and 2018-NN-152)Youth Innovation Promotion Association CAS(Nos.2019423 and 2018467)the National Natural Science Foundation of China(No.U1507120).
文摘Salt attack performance of magnesium oxychloride cement(MOC) in brine was investigated from the viewpoints of strength development and strength coefficient. Microstructure was studied using quantitative X-ray diffraction(QXRD), thermogravimetry(TG) and scanning electron microscopy(SEM). The results show that MOC mortars have outstanding salt attack performance after aging brine and raw brine immersion. The salt attack coefficients of MOC mortars are higher than 0.8, which is qualified for application in saline soil and salt lake area. The reason is that salt brine solution enters into the voids of MOC and plays a role of toughening and strengthening in the MOC.
基金the National Science Council (No. NSC-99-2219-E-033-001)the Foundation of the Chung Yuan Christian University (1004) (No. CYCU-EECS.9801)
文摘This paper aims at analyzing the security issues that lie in the application layer (AL) protocols when users connect to the Internet via a wireless local area network (WLAN) through an access point. When adversaries launch deauthentication flood attacks cutting users' connection, the connection managers will automatically research the last access point's extended service set identifier (ESSID) and then re-establish connection. However, such re-connection can lead the users to a fake access point with the same ESSID set by attackers. As the attackers hide behind users' access points, they can pass AL's authentication and security schemes, e.g. secure socket layer (SSL). We have proved that they can even spy on users' account details, passwords, data and privacy.
文摘[目的]DDoS攻击作为一种破坏性极强的网络威胁,严重影响电力系统的稳定运行。由于电力监控局域网中的数据流量复杂多变,DDoS攻击流量与正常流量在表现形式上存在较高相似性,导致二者难以有效区分。传统的静态阈值方法虽能在一定程度上实现流量监测,但因无法适应流量的动态变化,常出现误判,从而削弱了对DDoS攻击的检测效果,难以为电力监控局域网提供可靠的安全保障。为此,提出一种基于动态阈值的电力监控局域网DDoS攻击检测方法。[方法]通过网络流量采集设备实时获取电力监控局域网的流量数据,并利用信息熵理论计算流量熵值。信息熵可反映数据的混乱程度:正常流量通常具有一定规律性,熵值相对稳定;而DDoS攻击流量因异常数据包的大量涌入,导致熵值显著波动。基于此特性,本文设定动态阈值,当流量熵值超过阈值时判定为异常流量。随后,提取异常流量的六元组特征集(包括平均流包数、平均字节数、源IP地址增速、流表生存时间变化、端口增速以及对流比),并将其输入预训练的最小二乘支持向量机(least squares support vector machine,LSSVM)分类器中。LSSVM通过对已知样本的学习建立特征与类别的映射关系,从而实现对异常流量的分类与判断,确定其是否为DDoS攻击流量。[结果]实验结果表明,本文方法在ROC曲线和PR曲线上均表现较好,ROC-AUC和PR-AUC值均较传统方法有所提高。这表明该方法在检测DDoS攻击时具备更高的准确率与召回率,能够有效识别隐藏于正常流量中的攻击流量,并显著降低误判率。[结论]基于动态阈值与LSSVM分类器的检测方法能够有效应对电力监控局域网中DDoS攻击与正常流量难以区分的问题,提升检测的准确性与可靠性,为电力监控局域网提供更为有效的DDoS攻击防护手段,有助于增强电力系统的安全性与稳定性,保障电力供应的可靠运行,对电力行业网络安全防护具有重要的实际应用价值。
