Abstract
With the development of the Internet of Things and the pervasive use of internet service providers (ISPs), internet users and data have reached an unprecedented volume. However, the existence of malicious users seriously undermine user privacy and network security by distributing a large amount of unwanted traffic, such as spam, pop-up, and malware. This to some extent can be identified with the cooperation of individual users by installing anti-virus toolkits. However, users need to purchase such software at an additional cost. Therefore, unless built-in incentive mechanisms exist, rational users will choose not to install virus software. If enough network entities behave in this way, the network will be flooded with unwanted traffic. In this paper, we propose an evolutionary game theoretic incentive mechanism to promote the cooperation of individual users to curb the expansion of unwanted traffic. We propose a combined reward and punishment mechanism to further incentivize cooperative behavior. Meanwhile, the acceptance condition of our framework is analyzed and we carry out a number of simulations to evaluate the acceptance conditions of our framework.The experimental results indicate that our reward and punishment mechanism can efficiently incentivize users to adopt cooperative behavior and reduce unwanted traffic.
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Acknowledgements
This work is supported by the National Science Foundation of China (Grant No. 61802097), and the Natural Science Foundation of Jiangsu Province (No. BK20131277).
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Liu, J., Li, M., Alam, M. et al. A Game Theoretic Reward and Punishment Unwanted Traffic Control Mechanism. Mobile Netw Appl 24, 1279–1294 (2019). https://doi.org/10.1007/s11036-018-1166-0
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DOI: https://doi.org/10.1007/s11036-018-1166-0