Network Attack Intention Recognition Based on Signaling Game Model and Netlogo Simulation

Author(s):  
Xiaoning Zhang ◽  
Hengwei Zhang ◽  
Chenwei Li ◽  
Pengyu Sun ◽  
Zhilin Liu ◽  
...  
2021 ◽  
Vol 1955 (1) ◽  
pp. 012115
Author(s):  
Xiaoning Zhang ◽  
Hengwei Zhang ◽  
Pengyu Sun ◽  
Jindong Wang

2010 ◽  
Vol 121-122 ◽  
pp. 360-363
Author(s):  
Hai Dong Yu ◽  
Fang Liu ◽  
Yun Feng Luo

The paper researched the screening model in enterprise competitive intelligence activity based on game theory. It studied the service provider’s decision in competitive intelligence(CI) project and proved it could be satisfied with Bayesian Nash equilibrium. It also revealed the heterogeneity between the service providers through a signaling game model in which signal set was the combine of CI quality standard term. The result shows that a quality standard about CI should be designed in contract which provides a signal for service provider to self-certify its own true type and is in favor of screening for enterprise.


Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3014
Author(s):  
Pengxi Yang ◽  
Fei Gao ◽  
Hua Zhang

We formalize the adversarial process between defender and attackers as a game and study the non-cooperative evolutionary game mechanism under bounded rationality. We analyze the long-term dynamic process between the attacking and defending parties using the evolutionary stable strategies derived from the evolutionary game model. First, we construct a multi-player evolutionary game model consisting of a defender and multiple attackers, formally describe the strategies, and construct a three-player game payoff matrix. Then, we propose two punishment schemes, i.e., static and dynamic ones. Moreover, through the combination of mathematical derivation with simulation, we obtain the evolutionary stable strategies of each player. Different from previous work, in this paper, we consider the influence of strategies among different attackers. The simulation shows that (1) in the static punishment scheme, increasing the penalty can quickly control the occurrence of network attacks in the short term; (2) in the dynamic punishment scheme, the game can be stabilized effectively, and the stable state and equilibrium values are not affected by the change of the initial values.


Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 3963-3974 ◽  
Author(s):  
Guoxing Zhang ◽  
Zhenhua Zhang ◽  
Yongjing Cui ◽  
Chun Yuan

In recent years, greater efforts in tax preference policy for energy conservation and emission reduction (ECER) have been implemented in our country. Based on the tax preference of enterprise income for comprehensive utilization of resources, the constraints to achieve completely successful equilibrium are studied in the single period and multiple periods. In the single period, the key to achieve separating equilibrium is analyzed carefully by constructing a signaling game model of enterprises and government on tax preference of enterprise income. In the multiple periods, with the stochastic evolutionary game model based on the stochastic differential equation (SDE) theory, the constraints of keeping the separating equilibrium stable and continuing in a long term will be further investigated. It gives the optimal number of tax preference of enterprise income, camouflage cost and expected cost of risk under the state of separating equilibrium. The optimal result of completely successful equilibrium is obtained in single period by the analysis of numerical example for enterprises and government signaling game model. The simulation experiment is successfully finished to test the effectiveness of the stochastic evolutionary game model by using mathematical software MATLAB.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiaotong Xu ◽  
Gaocai Wang ◽  
Jintian Hu ◽  
Yuting Lu

In recent years, evolutionary game theory has been gradually applied to analyze and predict network attack and defense for maintaining cybersecurity. The traditional deterministic game model cannot accurately describe the process of actual network attack and defense due to changing in the set of attack-defense strategies and external factors (such as the operating environment of the system). In this paper, we construct a stochastic evolutionary game model by the stochastic differential equation with Markov property. The evolutionary equilibrium solution of the model is found and the stability of the model is proved according to the knowledge of the stochastic differential equation. And we apply the explicit Euler numerical method to analyze the evolution of the strategy selection of the players for different problem situations. The simulation results show that the stochastic evolutionary game model proposed in this paper can get a steady state and obtain the optimal defense strategy under the action of the stochastic disturbance factor. In addition, compared with other kinds of literature, we can conclude that the return on security investment of this model is better, and the strategy selection of the attackers and defenders in our model is more suitable for actual network attack and defense.


2010 ◽  
Vol 33 (9) ◽  
pp. 1748-1762 ◽  
Author(s):  
Yuan-Zhuo WANG ◽  
Chuang LIN ◽  
Xue-Qi CHENG ◽  
Bin-Xing FANG

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