Attack-Defense Game Model with Multi-Type Attackers Considering Information Dilemma

Today, people rely heavily on infrastructure networks. Attacks on infrastructure networks can lead to significant property damage and production stagnation. The game theory provides a suitable theoretical framework for solving the problem of infrastructure protection. Existing models consider only the beneficial effects that the defender obtains from information gaps. If the attacker's countermeasures are ignored, the defender will become passive. Herein, we consider that a proficient attacker with a probability in the game can fill information gaps in the network. First, we introduce the link-hiding rule and the information dilemma. Second, based on the Bayesian static game model, we establish an attack-defense game model with multiple types of attackers. In the game model, we consider resource-consistent and different types of distributions of the attacker. Then, we introduce the solution method of our model by combining the Harsanyi transformation and the bi-matrix game. Finally, we conduct experiments using a scale-free network. The result shows that the defender can be benefited by hiding some links when facing a normal attacker or by estimating the distribution of the attacker correctly. The defender will experience a loss if it ignores the proficient attacker or misestimates the distribution.

SINR-based power schedule of sensors and DoS attackers in wireless network

In this paper, the game theory approaches are used to solve the power schedule problem in the wireless communication network. All sensors can be affected by DoS attackers when transmitting data. The game process between sensors and attackers is established as Bayesian game process. First, a Nash Equilibrium (NE) framework is proposed based on the object function consist of signal-to-interference-and-noise-ratio (SINR). Second, the total power of sensors is considered to have two types, and each type has some power levels. Unlike NE, both sensors and attackers no longer learn the specific total power of each other. However, sensors and attackers can get the type distribution of each other. In this situation, the strategies of sensors and attackers are formulated by introducing the Harsanyi transformation, and the Bayesian Nash Equilibrium (BNE) is solved. Finally, the Bayesian equilibrium strategies used by both offensive and defensive players are compared in the numerical example, which can illustrate the advantage of making full use of incomplete information.

Priority-Aware Price-Based Power Control for Co-Located WBANs Using Stackelberg and Bayesian Games

According to the IEEE 802.15.6 standard, interference within each wireless body area network (WBAN) can be well addressed by the time division multiple access (TDMA)-based media access control (MAC) protocol. However, the inter-WBAN interference will be caused after multiple WBANs are gathered together. This paper proposes a priority-aware price-based power control (PPPC) scheme for mitigating the inter-WBAN interference. Specifically, to maximize the transmission data rate of sensors and control the aggregate interference suffered by coordinators, a Stackelberg game is established, in which the coordinators issue interference prices and the active sensors adjust their transmission power accordingly. On the other hand, since the information about the identities of the active sensors in a specific time slot is kept private, a Bayesian game is designed to model the interaction among sensors. Moreover, the timeliness and reliability of data transmission are guaranteed by designing the sensors’ priority factors and setting a priority-related active probability for each sensor. At last, a power control algorithm is designed to obtain optimal strategies of game players. Simulation results show that compared with other existing schemes, the proposed scheme achieves better fairness with a comparable network sum data rate and is more energy efficient.

Neurons and astrocytes interaction in neuronal network: A game-theoretic approach

A neuron is the fundamental unit of the nervous system and the brain, crucial for transducing information in form of trains of electrical pulses known as action potentials. The connection between neurons is through synapses, enabling communication between neurons. This communication link is one of the key elements in processing of information from a neuron to another neuron. The strength of the synapses may vary over time, a phenomenon known as synaptic plasticity. This is the process by which it is believed memory and learning is governed. Recent studies revealed environmental factors affect the strength of synapses, and the way neurons communicate to each other. This poses the question as to what extent the pre- and post- synaptic neurons sense the environmental changes, and in turn adjust their synaptic link. Here, we model the behavior of an interconnected neuronal network in various environmental conditions as a multi-agent system in a game theoretic framework. We focus on a CA1 lattice subfield as an example plastic neuronal network. Our analysis revealed the neuronal network converges to different equilibria depending on the environmental changes. The model well-predicts the behavior of the network compared to a well-known theoretical model of individual neurons.

Older People in the Platform Economy

Since the platform economies have emerged, there are many new ways how people can perform earning activities. These new opportunities concern older people too. However, some authors write that the actors of the platform economy are mainly younger people and it is not typical that older people work through platforms. We cite the opposite case of Oszkar (Hungarian On-line Passenger Intermediary System) where the ratio of older (55+) drivers to the total number of chauffeurs increased in time. At the same time, 30-40% of all drivers do not declare their age. In our paper, we analyse why older people do not declare their age. Using the results of our online survey and a Bayesian game theoretic model we prove that in the equilibrium state older people are frequently against letting others know their real age when they apply to work through a platform. We think that the cause is still existing age discrimination.