Non-cooperative uplink power control in cellular radio systems
Wireless Networks - Special issue transmitter power control
CDMA uplink power control as a noncooperative game
Wireless Networks
A Bayesian game approach for intrusion detection in wireless ad hoc networks
GameNets '06 Proceeding from the 2006 workshop on Game theory for communications and networks
Congestion games with malicious players
Proceedings of the 8th ACM conference on Electronic commerce
Journal of Computer Security - Special Issue on Security of Ad-hoc and Sensor Networks
A jamming game in wireless networks with transmission cost
NET-COOP'07 Proceedings of the 1st EuroFGI international conference on Network control and optimization
Optimal Jamming Attack Strategies and Network Defense Policies in Wireless Sensor Networks
IEEE Transactions on Mobile Computing
Utility-Optimal Random-Access Control
IEEE Transactions on Wireless Communications
Correlated jamming on MIMO Gaussian fading channels
IEEE Transactions on Information Theory
Game theory and the design of self-configuring, adaptive wireless networks
IEEE Communications Magazine
Game Theoretic Modeling of Malicious Users in Collaborative Networks
IEEE Journal on Selected Areas in Communications
Game theory for cyber security
Proceedings of the Sixth Annual Workshop on Cyber Security and Information Intelligence Research
Near-optimal deviation-proof medium access control designs in wireless networks
IEEE/ACM Transactions on Networking (TON)
Game theory meets network security and privacy
ACM Computing Surveys (CSUR)
A Security Differential Game Model for Sensor Networks in Context of the Internet of Things
Wireless Personal Communications: An International Journal
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We consider game theoretic models of wireless medium access control (MAC) in which each transmitter makes individual decisions regarding their power level or transmission probability. This allows for scalable distributed operation; however, it can also enable users to pursue malicious objectives such as jamming other nodes to deny them service. We study games with two types of players: selfish and malicious transmitters. Each type is characterized by a utility function depending on throughput reward and energy cost. Furthermore, we focus on the setting where the transmitters have incomplete information regarding other transmitters' types, modeled as probabilistic beliefs. We first analyze a power-controlled MAC game in which the nodes select powers for continuous transmissions and then extend this to a random access MAC in which nodes choose transmission probabilities. For each case, the Bayesian Nash equilibrium strategies are derived for different degrees of uncertainty, and the resulting equilibrium throughput of selfish nodes is characterized. We identify conditions in which the throughput improves with increasing type uncertainty and introduce Bayesian learning mechanisms to update the type beliefs in repeated games. For unknown types and costs, we also specify the equilibrium cut-off thresholds for monotonic transmission decisions. The analysis provides insights into the optimal defense mechanisms against denial of service attacks at the MAC layer in wireless networks.