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1.
Sci Rep ; 12(1): 15167, 2022 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-36071137

RESUMO

This research introduces a new combined modelling approach for mapping soil salinity in the Minab plain in southern Iran. This study assessed the uncertainty (with 95% confidence limits) and interpretability of two deep learning (DL) models (deep boltzmann machine-DBM) and a one dimensional convolutional neural networks (1DCNN)-long short-term memory (LSTM) hybrid model (1DCNN-LSTM) for mapping soil salinity by applying DeepQuantreg and game theory (Shapely Additive exPlanations (SHAP) and permutation feature importance measure (PFIM)), respectively. Based on stepwise forward regression (SFR)-a technique for controlling factor selection, 18 of 47 potential controls were selected as effective factors. Inventory maps of soil salinity were generated based on 476 surface soil samples collected for measuring electrical conductivity (ECe). Based on Taylor diagrams, both DL models performed well (RMSE < 20%), but the 1DCNN-LSTM hybrid model performed slightly better than the DBM model. The uncertainty range associated with the ECe values predicted by both models estimated using DeepQuantilreg were similar (0-25 dS/m for the 1DCNN-LSTM hybrid model and 2-27 dS/m for DBM model). Based on the SFR and PFIM (permutation feature importance measure)-a measure in game theory, four controls (evaporation, sand content, precipitation and vertical distance to channel) were selected as the most important factors for soil salinity in the study area. The results of SHAP (Shapely Additive exPlanations)-the second measure used in game theory-suggested that five factors (evaporation, vertical distance to channel, sand content, cation exchange capacity (CEC) and digital elevation model (DEM)) have the strongest impact on model outputs. Overall, the methodology used in this study is recommend for applications in other regions for mapping environmental problems.


Assuntos
Aprendizado Profundo , Solo , Teoria do Jogo , Salinidade , Areia , Incerteza
2.
Sci Rep ; 12(1): 15716, 2022 Sep 20.
Artigo em Inglês | MEDLINE | ID: mdl-36127449

RESUMO

The pandemic reminded us that the pathogen evolution still has a serious effect on human societies. States, however, can prepare themselves for the emergence of a novel pathogen with unknown characteristics by analysing potential scenarios. Game theory offers such an appropriate tool. In our game-theoretical framework, the state is playing against a pathogen by introducing non-pharmaceutical interventions to fulfil its socio-political goals, such as guaranteeing hospital care to all needed patients, keeping the country functioning, while the applied social restrictions should be as soft as possible. With the inclusion of activity and economic sector dependent transmission rate, optimal control of lockdowns and health care capacity management is calculated. We identify the presence and length of a pre-symptomatic infectious stage of the disease to have the greatest effect on the probability to cause a pandemic. Here we show that contrary to intuition, the state should not strive for the great expansion of its health care capacities even if its goal is to provide care for all requiring it and minimize the cost of lockdowns.


Assuntos
Doenças Transmissíveis , Teoria do Jogo , Humanos , Pandemias/prevenção & controle
3.
Comput Intell Neurosci ; 2022: 9544059, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36093481

RESUMO

Generally, system failures, such as crash failures, Byzantine failures, and so on, are considered as common reasons for the inconsistencies of distributed consensus and have been extensively studied. In fact, strategic manipulations by rational agents are not ignored for reaching consensus in a distributed system. In this paper, we extend the game-theoretic analysis of consensus and design an algorithm of rational uniform consensus with general omission failures under the assumption that processes are controlled by rational agents and prefer consensus. Different from crashing one, agent with omission failures may crash or omit to send or receive messages when it should, which leads to difficulty of detecting faulty agents. By combining the possible failures of agents at the both ends of a link, we convert omission failure model into link state model to make faulty detection possible. Through analyzing message passing mechanism in the distributed system with n agents, among which t agents may commit omission failures, we provide the upper bound on message passing time for reaching consensus on a state among nonfaulty agents and message chain mechanism for validating messages. Then, we prove that our rational uniform consensus is a Nash equilibrium when n > 2t + 1, and failure patterns and initial preferences are blind (an assumption of randomness). Thus, agents have no motivation to deviate the consensus, which could provide interpretable stability for the algorithm in multiagent systems such as distributed energy systems. Our research strengthens the reliability of consensus with omission failures from the perspective of game theory.


Assuntos
Algoritmos , Teoria do Jogo , Redes de Comunicação de Computadores , Consenso , Reprodutibilidade dos Testes
4.
Artigo em Inglês | MEDLINE | ID: mdl-36078759

RESUMO

In the context of China's "double carbon" target, an urgent problem that remains to be solved is how to drive the construction of an enterprise green innovation ecosystem through effective environmental regulations to alleviate the pressure of energy saving and emission reduction. Based on this, we constructed a tripartite evolutionary game model of enterprises, governments and financial institutions, and used the evolutionary game theory and MATLAB simulation to analyze the evolutionary process of the interaction of the subjects of the green technology innovation of enterprises under the dual environmental regulation. The research finds that: (1) Both formal and informal environmental regulations can promote green technology innovation in enterprises, provided that the enforcement is controlled within an appropriate range; (2) Informal environmental regulations are a weaker driver of green technology innovation in firms than formal environmental regulations; (3) Six types of environmental regulation strategies, namely, the "penalty enterprises mechanism", "financial support mechanism", "public supervision mechanism", "punishes financial institutions mechanism", "financial subsidy mechanism" and "carbon tax mechanism", have a decreasing effect on promoting the development of the green technology innovation ecosystem of enterprises; (4) Combining the implementation of a middle-intensity subsidy mechanism, a high-intensity penalty mechanism, a low-intensity public supervision mechanism and a middle-intensity carbon tax mechanism is the optimal strategy combination to encourage collaborative green technology innovation between companies and financial institutions.


Assuntos
Ecossistema , Invenções , Carbono , China , Teoria do Jogo , Governo , Humanos
5.
PLoS One ; 17(9): e0273961, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36048857

RESUMO

Although strategic coalition formation is traditionally modeled using cooperative game theory, behavioral game theorists have repeatedly shown that outcomes predicted by game theory are different from those generated by actual human behavior. To further explore these differences, in a cooperative game theory context, we experiment to compare the outcomes resulting from human participants' behavior to those generated by a cooperative game theory solution mechanism called the core partition. Our experiment uses an interactive simulation of a glove game, a particular type of cooperative game, to collect the participant's decision choices and their resultant outcomes. Two different glove games are considered, and the outputs from 62 trial games are analyzed. The experiment's outcomes show that core coalitions, which are coalitions in a core partition, are found in about 42% of games. Though this number may seem low, a trial's outcome is more complex than whether the human player finds a core coalition or not. Finding the core coalition depends on factors such as the other possible feasible solutions and the payoffs available from these solutions. These factors, and the complexity they generate, are discussed in the paper.


Assuntos
Teoria do Jogo , Análise de Sistemas , Simulação por Computador , Comportamento Cooperativo , Humanos
6.
Comput Intell Neurosci ; 2022: 9318475, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36120691

RESUMO

Vehicle networking and autonomous driving are hot areas of scientific research today, and they complement each other and play an important role in people's intelligent travel. Intelligent driving vehicle can enhance road safety, effectively reduce traffic flow and fuel consumption, and promote the overall social development. It has great application value in urban traffic system. The traffic condition of a city directly affects the economic development of the city and the improvement of people's quality of life. As the "core" of the urban traffic network, intersections are the frequent places where traffic jams occur. Game theory, as a win-win theory, mainly solves the problem of multiperson and multi-objective with contradictory objective functions and can be used to study the optimal signal control strategy. Aiming at this problem, the potential conflict behaviors of intelligent driving vehicles when turning left at urban intersections are analyzed and a decision model is established. A long-term trajectory prediction model of straight vehicles is established based on the Gaussian process regression model (GPR) considering the vehicle motion pattern. Combined with trajectory prediction, a decision-making process (model) for intelligent driving vehicles based on conflict resolution and a multifactor driving action selection method are proposed. A coordination algorithm based on game theory is designed for conflicting vehicles. The proposed algorithm is verified by the self-developed intelligent vehicle hardware simulation platform. The simulation results show that the PID method based on digital identification and positioning makes the intelligent vehicle obtain good system step response, can improve the disturbance tracking ability of intersection turning analysis, meet the requirements of turning control system, and reduce the complexity and randomness of parameter design, which is better than the traditional fuzzy control method.


Assuntos
Condução de Veículo , Qualidade de Vida , Algoritmos , Simulação por Computador , Teoria do Jogo , Humanos
7.
Math Biosci Eng ; 19(10): 10022-10036, 2022 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-36031981

RESUMO

Coinfection is the process of an infection of a single host with two or more pathogen variants or with two or more distinct pathogen species, which often threatens public health and the stability of economies. In this paper, we propose a novel two-strain epidemic model characterizing the co-evolution of coinfection and voluntary vaccination strategies. In the framework of evolutionary vaccination, we design two game rules, the individual-based risk assessment (IB-RA) updated rule, and the strategy-based risk assessment (SB-RA) updated rule, to update the vaccination policy. Through detailed numerical analysis, we find that increasing the vaccine effectiveness and decreasing the transmission rate effectively suppress the disease prevalence, and moreover, the outcome of the SB-RA updated rule is more encouraging than those results of the IB-RA rule for curbing the disease transmission. Coinfection complicates the effects of the transmission rate of each strain on the final epidemic sizes.


Assuntos
Coinfecção , Epidemias , Teoria do Jogo , Humanos , Vacinação
8.
Math Biosci Eng ; 19(10): 10493-10532, 2022 Jul 25.
Artigo em Inglês | MEDLINE | ID: mdl-36032004

RESUMO

This study aims to link two related social psychology concepts, self-awareness and politeness, with human helping behavior and demonstrate it from the perspective of psychological game theory. By establishing a game theory model, and adding politeness and self-awareness as influencing factors, the Bayesian Nash equilibrium clarified people's help-seeking and help-giving behavior. As a result, we explained the relationship between politeness, self-awareness, and the willingness of the help seekers, as well as the helpers, and we can thus understand why some people do not seek help or give help. Specifically, on the one hand, from the perspective of help seekers, we found that people with a high level of self-awareness and politeness tend not to ask others for help. On the other hand, from the perspective of helpers, we found that people with a high level of self-awareness and politeness tend to help others. To the best of our knowledge, this is the first application of Bayesian Nash equilibrium based on psychological game theory in studying human help-seeking and help-giving behavior.


Assuntos
Teoria do Jogo , Hepatopatia Gordurosa não Alcoólica , Teorema de Bayes , Humanos
9.
Bull Math Biol ; 84(10): 106, 2022 08 25.
Artigo em Inglês | MEDLINE | ID: mdl-36008498

RESUMO

COVID-19 epidemics exhibited multiple waves regionally and globally since 2020. It is important to understand the insight and underlying mechanisms of the multiple waves of COVID-19 epidemics in order to design more efficient non-pharmaceutical interventions (NPIs) and vaccination strategies to prevent future waves. We propose a multi-scale model by linking the behaviour change dynamics to the disease transmission dynamics to investigate the effect of behaviour dynamics on COVID-19 epidemics using game theory. The proposed multi-scale models are calibrated and key parameters related to disease transmission dynamics and behavioural dynamics with/without vaccination are estimated based on COVID-19 epidemic data (daily reported cases and cumulative deaths) and vaccination data. Our modeling results demonstrate that the feedback loop between behaviour changes and COVID-19 transmission dynamics plays an essential role in inducing multiple epidemic waves. We find that the long period of high-prevalence or persistent deterioration of COVID-19 epidemics could drive almost all of the population to change their behaviours and maintain the altered behaviours. However, the effect of behaviour changes fades out gradually along the progress of epidemics. This suggests that it is essential to have not only persistent, but also effective behaviour changes in order to avoid subsequent epidemic waves. In addition, our model also suggests the importance to maintain the effective altered behaviours during the initial stage of vaccination, and to counteract relaxation of NPIs, it requires quick and massive vaccination to avoid future epidemic waves.


Assuntos
COVID-19 , Epidemias , COVID-19/epidemiologia , COVID-19/prevenção & controle , Epidemias/prevenção & controle , Teoria do Jogo , Humanos , Conceitos Matemáticos , Modelos Biológicos
10.
Sci Rep ; 12(1): 13466, 2022 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-35931747

RESUMO

During a pandemic, isolating oneself from the community limits viral transmission and helps avoid repeated societal lockdowns. This entails a social dilemma-either distance oneself from others for the benefit of the public good or free-ride and enjoy the benefits of freedom. It is not yet understood how the unfamiliar incentive structure and interpersonal context presented by a pandemic together modulate individuals' approach to this social dilemma. In this preregistered study, we take a game-theoretical approach and investigate people's decisions to self-isolate, using a novel iterated multiplayer game designed to capture the decision-making environment in the pandemic. To elucidate players' thinking, we use a variation of the strategy method and elicit beliefs about how much others will self-isolate. Players tend to respond to social norms with abidance, rather than transgression; they resist the temptation to freeride when others are self-isolating. However, they deal with exponential growth poorly, as they only self-isolate sufficiently when lockdowns are imminent. Further, increased collective risk can motivate more self-isolation, even though the link between self-isolation and lockdowns is stochastic. Players underreport the influence of others' choices on their own, and underestimate others' self-isolation. We discuss implications for public health, and communication to the public.


Assuntos
Pandemias , Normas Sociais , Comunicação , Teoria do Jogo , Humanos
11.
PLoS One ; 17(8): e0273608, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36040912

RESUMO

We propose an evolutionary model for the emergence of shared linguistic convention in a population of agents whose social structure is modelled by complex networks. Through agent-based simulations, we show a process of convergence towards a common language, and explore how the topology of the underlying networks affects its dynamics. We find that small-world effects act to speed up convergence, but observe no effect of topology on the communicative efficiency of common languages. We further explore differences in agent learning, discriminating between scenarios in which new agents learn from their parents (vertical transmission) versus scenarios in which they learn from their neighbors (oblique transmission), finding that vertical transmission results in faster convergence and generally higher communicability. Optimal languages can be formed when parental learning is dominant, but a small amount of neighbor learning is included. As a last point, we illustrate an exclusion effect leading to core-periphery networks in an adaptive networks setting when agents attempt to reconnect towards better communicators in the population.


Assuntos
Evolução Biológica , Idioma , Comunicação , Teoria do Jogo , Linguística
12.
Proc Biol Sci ; 289(1980): 20220954, 2022 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-35946152

RESUMO

Interactions in social groups can promote behavioural specialization. One way this can happen is when individuals engage in activities with two behavioural options and learn which option to choose. We analyse interactions in groups where individuals learn from playing games with two actions and negatively frequency-dependent payoffs, such as producer-scrounger, caller-satellite, or hawk-dove games. Group members are placed in social networks, characterized by the group size and the number of neighbours to interact with, ranging from just a few neighbours to interactions between all group members. The networks we analyse include ring lattices and the much-studied small-world networks. By implementing two basic reinforcement-learning approaches, action-value learning and actor-critic learning, in different games, we find that individuals often show behavioural specialization. Specialization develops more rapidly when there are few neighbours in a network and when learning rates are high. There can be learned specialization also with many neighbours, but we show that, for action-value learning, behavioural consistency over time is higher with a smaller number of neighbours. We conclude that frequency-dependent competition for resources is a main driver of specialization. We discuss our theoretical results in relation to experimental and field observations of behavioural specialization in social situations.


Assuntos
Teoria do Jogo , Rede Social , Humanos , Reforço Psicológico
13.
J Math Biol ; 85(2): 19, 2022 08 03.
Artigo em Inglês | MEDLINE | ID: mdl-35920916

RESUMO

Evolutionary game theory is a powerful mathematical framework to study how phenotypes evolve by natural selection. Both birth and death are key in classic models in evolutionary games. The conflict between the two is fundamental in life history theory. The conflict between birth and death has been shown to change the evolutionary outcome for continuous traits. However, it is not clear how the conflict reshapes the evolutionary outcome for discrete strategies. An allocation model is proposed, in which part of the payoff is mapped to reproduction and the rest is mapped to illness. For non-evolving allocation, it is proved that the allocation does not change the fixation probability if and only if the illness is an inverse exponential function and the product of reproduction function and illness function is a constant. The necessary and sufficient condition implies that the allocation dramatically alters the evolutionary stability for a wide class of evolutionary processes. This is also verified by alternative construction proofs and numerical examples. Furthermore, the illness and reproduction function also ensures that every allocation is a neutral stable regime, if the allocation evolves to maximize the invasion probability. A deviation can lead to a non-trivial evolutionary branching. These results explicitly show that the reproduction and illness functions are restrictive to ensure the invariance of evolutionary outcome. Thus it implies that the demographic and life history need to be considered together to understand patterns of evolutionary dynamics.


Assuntos
Evolução Biológica , Teoria do Jogo , Fenótipo , Reprodução , Seleção Genética
14.
J R Soc Interface ; 19(193): 20220346, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35975562

RESUMO

Evolutionary game theory (EGT) is a branch of mathematics which considers populations of individuals interacting with each other to receive pay-offs. An individual's pay-off is dependent on the strategy of its opponent(s) as well as on its own, and the higher its pay-off, the higher its reproductive fitness. Its offspring generally inherit its interaction strategy, subject to random mutation. Over time, the composition of the population shifts as different strategies spread or are driven extinct. In the last 25 years there has been a flood of interest in applying EGT to cancer modelling, with the aim of explaining how cancerous mutations spread through healthy tissue and how intercellular cooperation persists in tumour-cell populations. This review traces this body of work from theoretical analyses of well-mixed infinite populations through to more realistic spatial models of the development of cooperation between epithelial cells. We also consider work in which EGT has been used to make experimental predictions about the evolution of cancer, and discuss work that remains to be done before EGT can make large-scale contributions to clinical treatment and patient outcomes.


Assuntos
Teoria do Jogo , Neoplasias , Evolução Biológica , Comportamento Cooperativo , Humanos , Mutação
15.
Proc Natl Acad Sci U S A ; 119(33): e2120120119, 2022 Aug 16.
Artigo em Inglês | MEDLINE | ID: mdl-35939706

RESUMO

Consider a cooperation game on a spatial network of habitat patches, where players can relocate between patches if they judge the local conditions to be unfavorable. In time, the relocation events may lead to a homogeneous state where all patches harbor the same relative densities of cooperators and defectors, or they may lead to self-organized patterns, where some patches become safe havens that maintain an elevated cooperator density. Here we analyze the transition between these states mathematically. We show that safe havens form once a certain threshold in connectivity is crossed. This threshold can be analytically linked to the structure of the patch network and specifically to certain network motifs. Surprisingly, a forgiving defector avoidance strategy may be most favorable for cooperators. Our results demonstrate that the analysis of cooperation games in ecological metacommunity models is mathematically tractable and has the potential to link topics such as macroecological patterns, behavioral evolution, and network topology.


Assuntos
Evolução Biológica , Comportamento Cooperativo , Ecossistema , Teoria do Jogo , Modelos Teóricos
16.
PLoS One ; 17(8): e0272719, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35944035

RESUMO

Most environments favor defection over cooperation due to natural selection. Nonetheless, the emergence of cooperation is omnipresent in many biological, social, and economic systems, quite contrary to the well-celebrated Darwinian theory of evolution. Much research has been devoted to better understanding how and why cooperation persists among self-interested individuals despite their competition for limited resources. Here we go beyond a single social dilemma since individuals usually encounter various social challenges. In particular, we propose and study a mathematical model incorporating both the prisoner's dilemma and the snowdrift game. We further extend this model by considering ecological signatures like mutation and selfless one-sided contribution of altruist free space. The nonlinear evolutionary dynamics that results from these upgrades offer a broader range of equilibrium outcomes, and it also often favors cooperation over defection. With the help of analytical and numerical calculations, our theoretical model sheds light on the mechanisms that maintain biodiversity, and it helps to explain the evolution of social order in human societies.


Assuntos
Comportamento Cooperativo , Teoria do Jogo , Evolução Biológica , Humanos , Mutação , Dilema do Prisioneiro
17.
Artigo em Inglês | MEDLINE | ID: mdl-35886416

RESUMO

As one of the most efficient means of emission reduction policies, carbon quota trading has a far-reaching impact on the carbon emission reduction of enterprises. Firstly, a two-party evolutionary game model of enterprise and government and a three-party evolutionary game model of enterprise-enterprise-government are constructed based on the multi-agent driving mechanism, evolutionary game theory, scenario simulation, and other methods. Then, we conduct a series of policy simulations for carbon emission under different scenario models and various enforcement strengths. Lastly, the behavioral strategies and system evolution trajectories in enterprises and government carbon trading are comprehensively investigated. The results show that in the two-party and three-party evolutionary game models, the carbon trading behavior is affected by the joint action of the enterprise and the government. The difference in initial willingness mainly affects the speed of the subject's convergence to the steady state. Based on this, policy suggestions are proposed, such as reducing the cost of carbon emission of enterprises, enhancing the vitality of carbon emission reduction of enterprises, and stimulating the power of government regulation and responsibility performance, which can provide suggestions for the development of the carbon market.


Assuntos
Carbono , Teoria do Jogo , China , Política Ambiental , Governo , Políticas
18.
Comput Intell Neurosci ; 2022: 1136601, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35795741

RESUMO

Despite a number of adverse factors, China's steel industry has maintained a rapid growth trend. China continues to consume two-thirds of the world's iron ore, the majority of which is imported. In this context, Chinese steel companies have begun to consider integrating their supply chains to increase efficiency and lower costs. However, the increasingly volatile international environment makes this an extremely risky proposition. As a result, the issue of how Chinese steel producers should participate in global supply chain integration has emerged as a critical research question that requires investigation. In this paper, we examine the supply chain integration problem using a typical China-Australia steel trade as an example. Specifically, we discuss in detail whether relevant firms should continue to promote supply chain integration in the Chinese-Australian steel industry, as well as the decision boundary of influence, using evolutionary game theory and policy risk cost factors. The empirical analysis demonstrates that policy risk has a range of effects on different types of steel firms. Even when international tensions are considered, smaller steel companies may retain a greater willingness to integrate their supply chains. Overall, the above findings can provide necessary decision support for enterprises to formulate supply chain management strategies.


Assuntos
Políticas , Aço , Austrália , China , Teoria do Jogo
19.
Artigo em Inglês | MEDLINE | ID: mdl-35886620

RESUMO

Current industrial development has led to an increase in sulfate-rich industrial sewage, threatening industrial ecology and the environment. Incorrectly treating high-concentration sulfate wastewater can cause serious environmental problems and even harm human health. Water with high sulfate levels can be treated as a resource and treated harmlessly to meet the needs of the circular economy. Today, governments worldwide are working hard to encourage the safe disposal and reuse of industrial salt-rich wastewater by recycling sulfate-rich wastewater (SRW) resources. However, the conflict of interests between the SRW production department, the SRW recycling department, and the governments often make it challenging to effectively manage sulfate-rich wastewater resources. This study aims to use the mechanism of evolutionary game theory (EGT) to conduct theoretical modelling and simulation analysis on the interaction of the behaviour of the above three participants. This paper focuses on the impact of government intervention and the ecological behaviour of wastewater producers on the behavioural decisions of recyclers. The results suggest that the government should play a leading role in developing the SRW resource recovery industry. SRW producers protect the environment in the mature stage, and recyclers actively collect and recover compliant sulfate wastewater resources. Governments should gradually deregulate and eventually withdraw from the market. Qualified recyclers and environmentally friendly wastewater producers can benefit from a mature SRW resources recovery industry.


Assuntos
Sulfatos , Águas Residuárias , Teoria do Jogo , Humanos , Reciclagem , Esgotos , Sulfatos/análise , Óxidos de Enxofre , Eliminação de Resíduos Líquidos/métodos , Águas Residuárias/análise
20.
Sensors (Basel) ; 22(14)2022 Jul 07.
Artigo em Inglês | MEDLINE | ID: mdl-35890796

RESUMO

The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV's openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities' areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework's credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the suggested framework achieves greater security and functionality characteristics and provides lower transaction and computation overhead than many of the available solutions so far. However, these solutions never considered the prime concerns of physical cloning and side-channel attacks. However, the framework in this paper is capable of handling them along with all the other security attacks the previous work can handle. Finally, the suggested framework has been subjected to a blockchain implementation to demonstrate its efficacy with duel gaming to achieve authentication in addition to its capability of using lower burdened blockchain at the physical layer, which current blockchain-based authentication models for IoVs do not support.


Assuntos
Blockchain , Segurança Computacional , Teoria do Jogo , Internet
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