• International journal of advanced smart convergence
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• v.13 no.3
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• pp.41-47
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• 2024

In this paper, we deal with a game theoretic problem to explore interactions between evasive Artificial Intelligence (AI) malware and detectors in Internet of Things (IoT). Evasive AI malware is defined as malware having capability of eluding detection by exploiting artificial intelligence such as machine learning and deep leaning. Detectors are defined as IoT devices participating in detection of evasive AI malware in IoT. They can be separated into two groups such that one group of detectors can be armed with detection capability powered by AI, the other group cannot be armed with it. Evasive AI malware can take three strategies of Non-attack, Non-AI attack, AI attack. To cope with these strategies of evasive AI malware, detector can adopt three strategies of Non-defense, Non-AI defense, AI defense. We formulate a Bayesian game theoretic model with these strategies employed by evasive AI malware and detector. We derive pure strategy Bayesian Nash Equilibria in a single stage game from the formulated Bayesian game theoretic model. Our devised work is useful in the sense that it can be used as a basic game theoretic model for developing AI malware detection schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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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.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.71-78
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• 2004

This paper presents a game-theoretic model of information transmission for variable message sign(VMS) operations. There are one VMS operator and many drivers as players. Operator wants to minimize the total travel time while the drivers want to minimize their own travel time. The operator who knows the actual traffic situation offers information strategically. The drivers evaluate the information from operator, and then choose the route. We model this situation as a cheap-talk game which is a simplest form of Bayesian game. We show that there is a possibility that the operator can improve the traffic efficiency by manipulating the electric signs at times. Indeed, it is an equilibrium of the game. This suggests that the operator must consider the strategic use of VMS system seriously.