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
Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harm...Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.展开更多
The concept of smart power requires to combine soft and hard power. Thus, smart power is a new approach for the US politics towards the Middle East. As a consequence of smart power politics of the US, some newly membe...The concept of smart power requires to combine soft and hard power. Thus, smart power is a new approach for the US politics towards the Middle East. As a consequence of smart power politics of the US, some newly members of the EU and Turkey has become a part of missile defense system. This is a significant indicator of usage of smart power for the EU members and Turkey. The security policies and practices of the US disclose a necessity for straight allies. For this reason, the relationship between the US, the EU and Turkey may be conceptualize with reference to the concept of smart power. In the case of Missile Defense System, Turkey has agreed to be a participant of this system after signing an agreement with the US. After that, Turkish government has confronted with some interior and exterior political difficulties. One of the most important difficulties is the interior resistance of missile defense system＇s Kiirecik Radar Station and its usage in Turkey. Another important point is the question of control of Turkish National Security and Defense strategy. In that respect, the US government＇s smart power applications may be included in the establishment of the radar station. The EU has also been included in that strategy. This paper will argue smart power practices of the US, the EU and Turkey with reference to comparative practices of power politics and the case of Missile Defense System. In this way, a comprehensive and system-type assessment of possible responses and the change in relations between stakeholder states not only in the issue of a set-up of a Turkish radar station, but on a broader range of international ＂hard＂ security balance will be demonstrated.展开更多
目前计算机网络防御研究中缺乏高层且易于细化的策略建模方法,因此在分析Or-BAC模型(Organization Based Access Control model)的基础上,对网络防御控制行为进行抽象,建立计算机网络防御策略模型(CNDPM,Computer Network Defense Polic...目前计算机网络防御研究中缺乏高层且易于细化的策略建模方法,因此在分析Or-BAC模型(Organization Based Access Control model)的基础上,对网络防御控制行为进行抽象,建立计算机网络防御策略模型(CNDPM,Computer Network Defense Policy Model).该模型对保护、检测和响应等策略进行统一建模,并引入角色、视图、活动自动分配的方法,以提高分配的效率,同时给出了策略到规则的推导规则,以细化为具体的防御规则.还给出了策略的完备性、有效性和一致性的形式化描述及分析.实例分析表明,该模型表示的计算机网络防御策略,能够有效地转化为防御规则,具有较好的实用性和扩展性.展开更多
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Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.
文摘The concept of smart power requires to combine soft and hard power. Thus, smart power is a new approach for the US politics towards the Middle East. As a consequence of smart power politics of the US, some newly members of the EU and Turkey has become a part of missile defense system. This is a significant indicator of usage of smart power for the EU members and Turkey. The security policies and practices of the US disclose a necessity for straight allies. For this reason, the relationship between the US, the EU and Turkey may be conceptualize with reference to the concept of smart power. In the case of Missile Defense System, Turkey has agreed to be a participant of this system after signing an agreement with the US. After that, Turkish government has confronted with some interior and exterior political difficulties. One of the most important difficulties is the interior resistance of missile defense system＇s Kiirecik Radar Station and its usage in Turkey. Another important point is the question of control of Turkish National Security and Defense strategy. In that respect, the US government＇s smart power applications may be included in the establishment of the radar station. The EU has also been included in that strategy. This paper will argue smart power practices of the US, the EU and Turkey with reference to comparative practices of power politics and the case of Missile Defense System. In this way, a comprehensive and system-type assessment of possible responses and the change in relations between stakeholder states not only in the issue of a set-up of a Turkish radar station, but on a broader range of international ＂hard＂ security balance will be demonstrated.
文摘目前计算机网络防御研究中缺乏高层且易于细化的策略建模方法,因此在分析Or-BAC模型(Organization Based Access Control model)的基础上,对网络防御控制行为进行抽象,建立计算机网络防御策略模型(CNDPM,Computer Network Defense Policy Model).该模型对保护、检测和响应等策略进行统一建模,并引入角色、视图、活动自动分配的方法,以提高分配的效率,同时给出了策略到规则的推导规则,以细化为具体的防御规则.还给出了策略的完备性、有效性和一致性的形式化描述及分析.实例分析表明,该模型表示的计算机网络防御策略,能够有效地转化为防御规则,具有较好的实用性和扩展性.
