• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.1
• /
• pp.238-242
• /
• 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)
• /
• v.13 no.11
• /
• pp.5631-5652
• /
• 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.

• Journal of Information Processing Systems
• /
• v.16 no.2
• /
• pp.318-328
• /
• 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)
• /
• v.8 no.6
• /
• pp.1926-1945
• /
• 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.

• Journal of Communications and Networks
• /
• v.17 no.1
• /
• pp.75-83
• /
• 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)
• /
• v.9 no.9
• /
• pp.3312-3334
• /
• 2015

In this paper, a mechanism for spectrum allocation in overlay cognitive radio networks is proposed. In overlay cognitive radio networks, the secondary users (SUs) must first sense the activity of primary users (PUs) to identify unoccupied spectrum bands. Based on their different contributions for the spectrum sensing, the SUs get payoffs that are computed by the fusion center (FC). The unoccupied bands will be auctioned and SUs are asked to bid using payoffs they earned or saved. Coalitions are allowed to form among SUs because each SU may only need a portion of the bands. We formulate the coalition forming process as a coalition forming game and analyze it by game theory. In the coalition formation game, debtor-creditor relationship may occur among the SUs because of their limited payoff storage. A debtor asks a creditor for payoff help, and in return provides the creditor with a portion of transmission time to relay data for the creditor. The negotiations between debtors and creditors can be modeled as a Bayesian game because they lack complete information of each other, and the equilibria of the game is investigated. Theoretical analysis and numerical results show that the proposed auction yields data rate improvement and certain fairness among all SUs.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.49 no.1
• /
• pp.53-58
• /
• 2012

With a game-theoretic view, p-persistence slotted ALOHA is structured as a non-cooperative game, in which a Nash equilibrium is sought to provide a value for the probability of attempting to deliver a packet. An expression of Nash equilibrium necessarily includes the number of active outer stations, which is hardly available in many practical applications. In this paper, we thus propose a Bayesian scheme of predicting the number of active outer stations prior to deciding whether to attempt to deliver a packet or not. Despite only requiring the minimal information that an outer station is genetically able to acquire by itself, the Bayesian scheme demonstrates the competitive predicting performance against a method which depends on heavy information.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.3
• /
• pp.542-559
• /
• 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.

• Journal of Communications and Networks
• /
• v.10 no.3
• /
• pp.268-286
• /
• 2008

In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.10
• /
• pp.4157-4175
• /
• 2020

Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.