Research on Active Defense Strategy of Counter DDoS Attacks Based on Differential Games Model

Author(s):  
Rui Guo ◽  
Guiran Chang ◽  
Yuhai Qin ◽  
Baojing Sun ◽  
Yifu Feng ◽  
...  
Author(s):  
Rui Guo ◽  
Guiran Chang ◽  
Yuhai Qin ◽  
Baojing Sun ◽  
An Liu ◽  
...  

2020 ◽  
Vol 10 (2) ◽  
pp. 672
Author(s):  
Xin-Rui Liu ◽  
Hao Wang ◽  
Qiu-Ye Sun ◽  
Peng Jin

With the continuous development of the active distribution network (ADN), the problem of security and stability has become increasingly prominent. From the perspective of improving the defense capability of ADN, a new a multi-angle dynamic risk assessment index system based on the comprehensive vulnerability rate model is proposed in this paper. Risk threshold is used to monitor the status of the distribution network, which determine whether ADN needs to enter the active defense period. The minimum amount of load shedding outside the fault isolation region is regarded as the objective function, considering other constraints such as limited resources, the coordinated active defense strategy (CADS) is formed in this paper. Finally, the accuracy of the comprehensive vulnerability rate and the risk assessment value are verified by example analysis, and the superiority of the CADS is verified by comparing different defense strategies.


2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Xiaohu Liu ◽  
Hengwei Zhang ◽  
Yuchen Zhang ◽  
Lulu Shao ◽  
Jihong Han

Most network security research studies based on signaling games assume that either the attacker or the defender is the sender of the signal and the other party is the receiver of the signal. The attack and defense process is commonly modeled and analyzed from the perspective of one-way signal transmission. Aiming at the reality of two-way signal transmission in network attack and defense confrontation, we propose a method of active defense strategy selection based on a two-way signaling game. In this paper, a two-way signaling game model is constructed to analyze the network attack and defense processes. Based on the solution of a perfect Bayesian equilibrium, a defense strategy selection algorithm is presented. The feasibility and effectiveness of the method are verified using examples from real-world applications. In addition, the mechanism of the deception signal is analyzed, and conclusions for guiding the selection of active defense strategies are provided.


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