• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.238-242
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• 2021

Game theory has been regarded as a useful theoretical tool for modeling the interactions between distinct entities and thus it has been harnessed in various research field. In particular, research attention has been shown to how to apply game theory to modeling the interactions between malign and benign entities in the field of wireless networks. Although various game theoretic modeling work have been proposed in the field of wireless networks, our proposed work is disparate to the existing work in the sense that we focus on mobile malign node detection problem in static wireless sensor networks. More specifically, we propose a Bayesian game theoretic modeling for mobile malign node detection problem in static wireless sensor networks. In our modeling, we formulate a two-player static Bayesian game with imperfect information such that player 1 is aware of the type of player 2, but player 2 is not aware of the type of player 1. We use four strategies in our static Bayesian game. We obtain Bayesian Nash Equilibria with pure strategies under certain conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• 대한전자공학회논문지TC
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• 제49권1호
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• pp.53-58
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• 2012

게임 이론적 시각으로 p-persistence 슬롯화된 ALOHA를 비협력 게임으로 구성하고, 이 게임에서 Nash equilibrium을 구해 찾아 패킷 전달을 시도할 확률 값을 마련한다. Nash equilibrium의 수학적 표현에는 반드시 활성 변방국의 수가 포함되지만, 많은 실제 응용에서 이러한 수를 거의 알 수가 없다. 따라서 본 논문에서는 패킷의 전달을 시도할 지 결정하기에 앞서 활성 변방국의 수를 예측하는 Bayes 풍의 방식을 제안한다. 제안하는 Bayes 풍의 방식은 변방국이 스스로 자연스럽게 구할 수 있는 최소 정보만을 필요로 하지만 상당량의 정보에 의존하는 방식에 비해 경쟁력 있는 예측 성능을 보여 준다.

• 한국게임학회 논문지
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• 제11권6호
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• pp.53-60
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• 2011

게임 서비스를 위한 소프트웨어의 경우 그 신뢰도에 대한 중요성은 지속적으로 증가하고 있다. 따라서 소프트웨어 신뢰도에 대한 평가 또한 매우 중요하다. 본 연구에서는 개발 공정에 대한 대표 활동인 확인 및 검증이 소프트웨어 신뢰도에 어떠한 영향을 미치는가를 정량적으로 분석하기 위하여 실험을 수행하였다. 이러한 실험 결과는, BBN (Bayesian Belief Network) 기반 신뢰도 평가와 같이, 개발 공정에 근거하여 신뢰도를 평가할 때 매우 유용한 근거 자료로 활용될 것이다.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.318-328
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• 2020

Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5819-5840
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• 2018

Considering the topology of hierarchical tree structure, each cluster in WSNs is faced with various attacks launched by malicious nodes, which include network eavesdropping, channel interference and data tampering. The existing intrusion detection algorithm does not take into consideration the resource constraints of cluster heads and sensor nodes. Due to application requirements, sensor nodes in WSNs are deployed with approximately uncorrelated security weights. In our study, a novel and versatile intrusion detection system (IDS) for the optimal defense strategy is primarily introduced. Given the flexibility that wireless communication provides, it is unreasonable to expect malicious nodes will demonstrate a fixed behavior over time. Instead, malicious nodes can dynamically update the attack strategy in response to the IDS in each game stage. Thus, a multi-stage intrusion detection game (MIDG) based on Bayesian rules is proposed. In order to formulate the solution of MIDG, an in-depth analysis on the Bayesian equilibrium is performed iteratively. Depending on the MIDG theoretical analysis, the optimal behaviors of rational attackers and defenders are derived and calculated accurately. The numerical experimental results validate the effectiveness and robustness of the proposed scheme.

• Journal of Communications and Networks
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• 제17권1호
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• pp.75-83
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• 2015

In mobile ad-hoc networks (MANETs), nodes are mobile in nature. Collaboration between mobile nodes is more significant in MANETs, which have as their greatest challenges vulnerabilities to various security attacks and an inability to operate securely while preserving its resources and performing secure routing among nodes. Therefore, it is essential to develop an effective secure routing protocol to protect the nodes from anonymous behaviors. Currently, game theory is a tool that analyzes, formulates and solves selfishness issues. It is seldom applied to detect malicious behavior in networks. It deals, instead, with the strategic and rational behavior of each node. In our study,we used the dynamic Bayesian signaling game to analyze the strategy profile for regular and malicious nodes. This game also revealed the best actions of individual strategies for each node. Perfect Bayesian equilibrium (PBE) provides a prominent solution for signaling games to solve incomplete information by combining strategies and payoff of players that constitute equilibrium. Using PBE strategies of nodes are private information of regular and malicious nodes. Regular nodes should be cooperative during routing and update their payoff, while malicious nodes take sophisticated risks by evaluating their risk of being identified to decide when to decline. This approach minimizes the utility of malicious nodes and it motivates better cooperation between nodes by using the reputation system. Regular nodes monitor continuously to evaluate their neighbors using belief updating systems of the Bayes rule.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권6호
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• pp.1926-1945
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• 2014

In this paper, we propose a distributed signal subspace interference alignment algorithm for single beam K-user ($3K{\geq}$) MIMO interference channel based on sum rate maximization and game theory. A framework of game theory is provided to study relationship between interference signal subspace and altruistic-egoistic bayesian game cost function. We demonstrate that the asymptotic interference alignment under proposed scheme can be realized through a numerical algorithm using local channel state information at transmitters and receivers. Simulation results show that the proposed scheme can achieve the total degrees of freedom that is equivalent to the Cadambe-Jafar interference alignment algorithms with perfect channel state information. Furthermore, proposed scheme can effectively minimize leakage interference in desired signal subspace at each receiver and obtain a moderate average sum rate performance compared with several existing interference alignment schemes.

• 한국경영과학회지
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• 제22권3호
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• pp.113-143
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• 1997

Most of the conflict problems between 2 persons can be represented as a bi-matrix game, because player's utilities, in general, are non-zero sum and change according to the progress of game. In the bi-matrix game the equilibrium point set which satisfies the Pareto optimality can be a good bargaining or coordination solution. Under the condition of incomplete information about the risk attitudes of the players, the bargaining or coordination solution depends on additional elements, namely, the players' methods of making inferences when they reach a node in the extensive form of the game that is off the equilibrium path. So the investigation about the players' inference type and its effects on the solution is essential. In addition to that, the effect of an individual's aversion to risk on various solutions in conflict problems, as expressed in his (her) utility function, must be considered. Those kinds of incomplete information make decision maker Bayesian, since it is often impossible to get correct information for building a decision making model. In Baysian point of view, this paper represents an analytic frame for guessing and learning opponent's attitude to risk for getting better reward. As an example for that analytic frame. 2 persons'bi-matrix game is considered. This example explains that a bi-matrix game can be transformed into a kind of matrix game through the players' implicitly cooperative attitude and the need of arbitration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권3호
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• pp.542-559
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• 2011

Most game-theoretic works of Aloha have emphasized investigating Nash equilibria according to the system state represented by the number of network users and their decisions. In contrast, we focus on the possible change of nodes' utility state represented by delay constraint and decreasing utility over time. These foregone changes of nodes' state are more likely to instigate selfish behaviors in networking environments. For such environment, in this paper, we propose a repeated Bayesian slotted Aloha game model to analyze the selfish behavior of impatient users. We prove the existence of Nash equilibrium mathematically and empirically. The proposed model enables any type of transmission probability sequence to achieve Nash equilibrium without degrading its optimal throughput. Those Nash equilibria can be used as a solution concept to thwart the selfish behaviors of nodes and ensure the system stability.