The Experts below are selected from a list of 12405 Experts worldwide ranked by ideXlab platform

Zakaria Dalil - One of the best experts on this subject based on the ideXlab platform.

  • intrusion detection model of wireless sensor networks based on Game theory and an autoregressive model
    Information Sciences, 2019
    Co-Authors: Lansheng Han, Man Zhou, Wenjing Jia, Zakaria Dalil
    Abstract:

    Abstract An effective security strategy for Wireless Sensor Networks (WSNs) is imperative to counteract security threats. Meanwhile, energy consumption directly affects the network lifetime of a wireless sensor. Thus, an attempt to exploit a low-consumption Intrusion Detection System (IDS) to detect malicious attacks makes a lot of sense. Existing Intrusion Detection Systems can only detect specific attacks and their network lifetime is short due to their high energy consumption. For the purpose of reducing energy consumption and ensuring high efficiency, this paper proposes an intrusion detection model based on Game theory and an autoregressive model. The paper not only improves the autoregressive theory model into a non-cooperative, complete-information, Static Game model, but also predicts attack pattern reliably. The proposed approach improves on previous approaches in two main ways: (1) it takes energy consumption of the intrusion detection process into account, and (2) it obtains the optimal defense strategy that balances the system’s detection efficiency and energy consumption by analyzing the model’s mixed Nash equilibrium solution. In the simulation experiment, the running time of the process is regarded as the main indicator of energy consumption of the system. The simulation results show that our proposed IDS not only effectively predicts the attack time and the next targeted cluster based on the Game theory, but also reduces energy consumption.

Ekram Hossain - One of the best experts on this subject based on the ideXlab platform.

  • competitive spectrum sharing in cognitive radio networks a dynamic Game approach
    IEEE Transactions on Wireless Communications, 2008
    Co-Authors: Dusit Niyato, Ekram Hossain
    Abstract:

    "Cognitive radio" is an emerging technique to improve the utilization of radio frequency spectrum in wireless networks. In this paper, we consider the problem of spectrum sharing among a primary user and multiple secondary users. We formulate this problem as an oligopoly market competition and use a noncooperative Game to obtain the spectrum allocation for secondary users. Nash equilibrium is considered as the solution of this Game. We first present the formulation of a Static Game for the case where all secondary users have the current information of the adopted strategies and the payoff of each other. However, this assumption may not be realistic in some cognitive radio systems. Therefore, we consider the case of bounded rationality in which the secondary users gradually and iteratively adjust their strategies based on the observations on their previous strategies. The speed of adjustment of the strategies is controlled by the learning rate. The stability condition of the dynamic behavior for this spectrum sharing scheme is investigated. The numerical results reveal the dynamics of distributed dynamic adaptation of spectrum sharing strategies.

Patrick Bajari - One of the best experts on this subject based on the ideXlab platform.

  • estimating Static models of strategic interaction
    Research Papers in Economics, 2006
    Co-Authors: Patrick Bajari, Han Hong, John Krainer, Denis Nekipelov
    Abstract:

    We propose a method for estimating Static Games of incomplete information. A Static Game is a generalization of a discrete choice model, such as a multinomial logit or probit, which allows the actions of a group of agents to be interdependent. Unlike most earlier work, the method we propose is semiparametric and does not require the covariates to lie in a discrete set. While the estimator we propose is quite flexible, we demonstrate that in most cases it can be easily implemented using standard statistical packages such as STATA. We also propose an algorithm for simulating the model which finds all equilibria to the Game. As an application of our estimator, we study recommendations for high technology stocks between 1998-2003. We find that strategic motives, typically ignored in the empirical literature, appear to be an important consideration in the recommendations submitted by equity analysts.

  • estimating Static models of strategic interaction
    Social Science Research Network, 2006
    Co-Authors: Patrick Bajari, Han Hong, John Krainer, Denis Nekipelov
    Abstract:

    We propose a method for estimating Static Games of incomplete information. A Static Game is a generalization of a discrete choice model, such as a multinomial logit or probit, which allows the actions of a group of agents to be interdependent. Unlike most earlier work, the method we propose is semiparametric and does not require the covariates to lie in a discrete set. While the estimator we propose is quite flexible, we demonstrate that in most cases it can be easily implemented using standard statistical packages such as STATA. We also propose an algorithm for simulating the model which finds all equilibria to the Game. As an application of our estimator, we study recommendations for high technology stocks between 1998-2003. We find that strategic motives, typically ignored in the empirical literature, appear to be an important consideration in the recommendations submitted by equity analysts.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Klaus Deininger - One of the best experts on this subject based on the ideXlab platform.

  • how important are endogenous peer effects in group lending estimating a Static Game of incomplete information
    Journal of Applied Econometrics, 2013
    Co-Authors: Yanyan Liu, Klaus Deininger
    Abstract:

    SUMMARY We quantify the importance of endogenous peer effects in group lending programs by estimating a Static Game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich dataset from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The preferred model suggests that the probability of a member making a full repayment would be 12 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity. Copyright © 2012 John Wiley & Sons, Ltd.

  • how important are endogenous peer effects in group lending estimating a Static Game of incomplete information
    Social Science Research Network, 2009
    Co-Authors: Yanyan Liu, Klaus Deininger
    Abstract:

    We quantify the importance of endogenous peer effects in group lending programs by estimating a Static Game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich data set from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The benchmark model suggests that the probability of a member making a full repayment would be 11 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity.

  • how important are peer effects in group lending estimating a Static Game of incomplete information
    Research Papers in Economics, 2009
    Co-Authors: Yanyan Liu, Klaus Deininger
    Abstract:

    We quantify the importance of peer effects in group lending by estimating a Static Game of incomplete information. In our model, group members make their repayment decisions simultaneously based on their household and loan characteristics as well as their expectations on other members' repayment decisions. Exploiting a rich data set of a microfinance program in India, our estimation results suggest that the probability of a member making a full repayment would be 15 percentage points higher if all the other fellow members make full repayment compared to the case where none of the other members repay in full. We also find that large inconsistencies exist in the estimated effects of other variables in models that do not incorporate peer effects and control for unobserved heterogeneity.

  • how important are peer effects in group lending estimating a Static Game of incomplete information
    2009 Annual Meeting July 26-28 2009 Milwaukee Wisconsin, 2009
    Co-Authors: Yanyan Liu, Klaus Deininger
    Abstract:

    We quantify the importance of peer effects in group lending by estimating a Static Game of incomplete information. In our model, group members make their repayment decisions simultaneously based on their household and loan characteristics as well as their expectations on other members’ repayment decisions. Exploiting a rich data set of a microfinance program in India, our estimation results suggest that the likelihood of a member making a full repayment would be 15 percent higher on average if all the other follow members make full repayment compared to the case where none of the other members repay in full. We also find that large inconsistencies exist in the estimated effects of other variables in models that do not incorporate peer effects and control for unobserved heterogeneity.

Yuchen Zhang - One of the best experts on this subject based on the ideXlab platform.

  • attack defense differential Game model for network defense strategy selection
    IEEE Access, 2019
    Co-Authors: Heng-wei Zhang, Jin-dong Wang, Lv Jiang, Shirui Huang, Yuchen Zhang
    Abstract:

    The existing Game-theoretic approaches for network security problems mostly use the Static Game or the multi-stage dynamic Game. However, these researches can not meet the timeliness requirment to analyze the network attack and defense. It is better to regard the attack and defense as a dynamic and real-time process, in which way the rapidity and continuity of network confrontation can be described more precisely. Referring to the epidemic model SIR, we formulated the novel model NIRM to analyze the evolution of network security states. Based on the mentioned above, the attack-defense differential Game model was constructed by introducing the differential Game theory. Then we figured out the solution of saddle-point strategies in the Game. By analyzing the Game equilibrium, the algorithm of optimal defense strategies selection in the real-time confrontation was designed, which is more targeted and has greater timeliness. Finally by simulation experiments, we demonstrated the validity of the model and method proposed in this paper, and drew some instructive conclusions on network defense deployment.