Visible to the public Game Theoretic Approaches

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Game Theoretic Approaches

Game theory has historically been the provenance of social sciences such as economics, political science, and psychology. Game theory has developed into an umbrella term for the logical side of science that includes both human and non-human actors like computers. It has been used extensively in wireless networks research to develop understanding of stable operation points for networks made of autonomous/selfish nodes. The nodes are considered as the players. Utility functions are often chosen to correspond to achieved connection rate or similar technical metrics. In security, the computer game framework is used to anticipate and analyze intruder and administrator concurrent interactions within the network. Research cited here includes articles on attacker-defender strategies and in modeling behaviors in a range of applications.

  • "DGM approach to network attacker and defender strategies," Kayode, Alese Boniface; Babatunde, Iwasokun Gabriel; Haruna Danjuma Israel, Information Science and Technology (ICIST), 2013 International Conference on , pp.313,320, 23-25 March 2013. (ID#:14-1316) Available at: This paper addresses the present problem with using a computer game framework to predict and interpret both malicious and authorized parties activity within the network, a challenge largely because this method requires prior knowledge of the network services. The authors of this paper propose their method of computer network security analysis, based on Deterministic Game-Theoretic Modeling (DGM). In this method, a two-person game is simulated, with attacker and defender displaying likely attacks and counterattacks, with the value of the game determined by using a saddle-point solution.
  • "Towards mathematical modelling in security risk management in system engineering," Hird, J.; Koelle, R.; Kolev, D., Integrated Communications, Navigation and Surveillance Conference (ICNS), 2013 pp.1,13, 22-25 April 2013. (ID#:14-1317) Available at: This paper proposes the potential use of mathematical modeling as a solution to SESAR is current security risk management method. For security control implementation with limited resources, only top priority actors and concepts will be allotted resource-intensive security risk assessment. This paper's proposed method is based on game theory and graph theory concepts, with risk mitigation decision-making modeled as a multi-objective optimization challenge.
  • "Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey," Mukherjee, A.; Fakoorian, S.; Huang, J.; Swindlehurst, A.; Communications Surveys & Tutorials, IEEE , vol.PP, no.99, pp.1,24 (ID#:14-1318) Available at: This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers, without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical layer message authentication is also briefly introduced. The survey concludes with observations on potential research directions in this area.
  • "Sourcing Strategies for Energy-Efficient Virtual Organisations in Cloud Computing," Widmer, T.; Premm, M.; Karaenke, P., Business Informatics (CBI), 2013 IEEE 15th Conference on , pp.159,166, 15-18 July 2013. (ID#:14-1319) Available at: Energy efficiency is an important managerial variable in service business models. Cloud computing advocates the innovation and design of open software services. How the supply of energy-aware software services affects the outsourcing strategies of IT businesses, however, is still not known. This research is concerned with the formation of green virtual organisations (GVOs). Such GVOs foster novel business models to enable the commercialisation of "green" software services. We approach the formation problem from a game-theoretic perspective, which provides well suited models for analysing sourcing strategies of service customers. For analysing the formation, we particularly study the social welfare by examining the economic and ecological efficiency of the GVO as a whole. The contribution of our research is an agent-based GVO formation mechanism that optimises the social welfare of service providers and customers. We demonstrate the efficacy of the proposed artifact in a set of simulation experiments.
  • "Distributed Learning-Based Spectrum Allocation with Noisy Observations in Cognitive Radio Networks," Derakhshani, M.; Le-Ngoc, T., Vehicular Technology, IEEE Transactions on , vol.PP, no.99, pp.1,1 (ID#:14-1320) Available at: This paper studies the medium access design for secondary users (SUs) from a game-theoretic learning perspective. In consideration of the random return of primary users, a distributed SU access approach is presented based on an adaptive CSMA scheme, in which each SU accesses multiple idle frequency slots of a licensed frequency band with adaptive activity factors. The problem of finding optimal activity factors of SUs is formulated as a potential game, and the existence, feasibility and optimality of Nash Equilibrium (NE) are analyzed. Furthermore, to achieve NEs of the formulated game, learning-based algorithms are developed in which each SU independently adjusts its activity factors. Convergence properties of best-response dynamics and log-linear dynamics are studied. Subsequently, by learning other SUs' behavior from locally available information, the convergence with probability 1 to an arbitrarily small neighborhood of the globally optimal solution is investigated by both analysis and simulation.
  • Dejun Yang; Guoliang Xue; Xi Fang; Misra, S.; Jin Zhang, "A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks," Networking, IEEE/ACM Transactions on , vol.21, no.6, pp.1947,1959, Dec. 2013. (ID#:14-1321) Available at: In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms.


Articles listed on these pages have been found on publicly available internet pages and are cited with links to those pages. Some of the information included herein has been reprinted with permission from the authors or data repositories. Direct any requests via Email to SoS.Project (at) for removal of the links or modifications to specific citations. Please include the ID# of the specific citation in your correspondence.