Game theory-based attack and defense analysis in virtual wireless networks with jammers and eavesdroppers

Abstract Dynamic spectrum sharing and cognitive radio networks were proposed to enhance the Radio Frequency (RF) spectrum utilization. However thee are several challenges to realize them in real systems, such as sensing uncertainty causing issues to licensed users, business models for licensed service providers. Wireless virtualization is regarded as a technology that leverages service level agreements to sublease unused or underutilized RF spectrum that addresses aforementioned issues and helps to significantly enhance the utilization of the RF spectrum, offer improved coverage and capacity of networks, enhance network security and reduce energy consumption. With wireless virtualization, wireless networks’ physical substrate is shared and reconfigured dynamically between virtual wireless networks through Mobile Virtual Network Operations (MVNOs). Wireless virtualization with dynamic configurable features of Wireless Infrastructure Providers (WIPs), virtualized wireless networks are vulnerable to a multitude of attacks, including jamming attacks and eavesdropping attacks. This paper investigates a means of defense through the employment of coalition game theory when jammers try to degrade the signal quality of legitimate users, and eavesdroppers aim to reduce secrecy rates. Specifically, we consider a virtual wireless network where MVNO users’ job is to improve their Signal to Interference plus Noise Ratio (SINR) while the jammers target to collectively enhance their Jammer Received Signal Strength (JRSS), and eavesdropper’s goal is to reduce the overall secrecy rate. Numerical results have demonstrated that the proposed game strategies are effective (in terms of data rate, secrecy rate and latency) against such attackers compared to the traditional approaches.

[1]  Eitan Altman,et al.  A Jamming Game in Wireless Networks with Transmission Cost , 2007, NET-COOP.

[2]  Tobias Galla,et al.  Two-population replicator dynamics and number of Nash equilibria in matrix games , 2006, q-bio/0608032.

[3]  Moses Garuba,et al.  Maximizing Secrecy Rate and Payoff Through Wireless Virtualization in Heterogeneous Wireless Networks , 2019, 2019 International Conference on Computing, Networking and Communications (ICNC).

[4]  Danda B. Rawat,et al.  Wireless Virtualization Architecture: Wireless Networking for Internet of Things , 2020, IEEE Internet of Things Journal.

[5]  F. Richard Yu,et al.  Wireless Network Virtualization: A Survey, Some Research Issues and Challenges , 2015, IEEE Communications Surveys & Tutorials.

[6]  Dusit Niyato,et al.  A game theoretic analysis of service competition and pricing in heterogeneous wireless access networks , 2008, IEEE Transactions on Wireless Communications.

[7]  Hsiao-Chun Wu,et al.  Physical layer security in wireless networks: a tutorial , 2011, IEEE Wireless Communications.

[8]  Narayan B. Mandayam,et al.  Evolutionary game theoretic analysis of distributed denial of service attacks in a wireless network , 2016, 2016 Annual Conference on Information Science and Systems (CISS).

[9]  Srikanth V. Krishnamurthy,et al.  Denial of Service Attacks in Wireless Networks: The Case of Jammers , 2011, IEEE Communications Surveys & Tutorials.

[10]  Danda B. Rawat,et al.  On the wireless virtualization with QoE constraints , 2019, Trans. Emerg. Telecommun. Technol..

[11]  Yinfeng Wu,et al.  Reliable routing in wireless sensor networks based on coalitional game theory , 2016, IET Commun..

[12]  Savo Glisic,et al.  Stochastic Models of Coalition Games for Spectrum Sharing in Large Scale Interference Channels , 2011, 2011 IEEE International Conference on Communications (ICC).

[13]  Danda B. Rawat,et al.  Wireless network virtualization for enhancing security: Status, challenges and perspectives , 2016, SoutheastCon 2016.

[14]  T. Başar,et al.  Coalitional Game Theory for Communication Networks: A Tutorial , 2009, ArXiv.

[15]  Danda B. Rawat,et al.  Payoff Optimization Through Wireless Network Virtualization for IoT Applications: A Three Layer Game Approach , 2019, IEEE Internet of Things Journal.

[16]  J M Smith,et al.  Evolution and the theory of games , 1976 .

[17]  Athanasios V. Vasilakos,et al.  Evolutionary coalitional games: design and challenges in wireless networks , 2012, IEEE Wireless Communications.

[18]  Xinbing Wang,et al.  Coalitional Game Theoretic Approach for Secondary Spectrum Access in Cooperative Cognitive Radio Networks , 2011, IEEE Transactions on Wireless Communications.

[19]  Dilip Krishnaswamy,et al.  Game theoretic formulations for network-assisted resource management in wireless networks , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[20]  N. Mandayam,et al.  Coalitional Games in Receiver Cooperation for Spectrum Sharing , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[21]  Zhu Han,et al.  Game-theoretic resource allocation methods for device-to-device communication , 2014, IEEE Wireless Communications.

[22]  Zhu Han,et al.  Coalitional game theory for communication networks , 2009, IEEE Signal Processing Magazine.

[23]  Sachin Shetty,et al.  Dynamic Spectrum Access for Wireless Networks , 2015, SpringerBriefs in Electrical and Computer Engineering.