Abstract
The wide application use of network systems extends people’s ability to access information, but its inherent network characteristics make it more vulnerable to DDoS attacks. Existing intrusion detection in network systems is usually only targeted at specific attacks, but will fail when dealing with strategic attacks. Therefore, based on game theory, the attack and defense process in the network system is analyzed, and the personalized DDoS attack detection is proposed. Considering that the attacker will observe the defender’s strategy before launching attacks, we model this problem as a Stackelberg security game and derive the optimal defensive strategy for the network system. After comparing the strategy with other non-strategic strategies, it is proved that our proposed method is more effective for detecting DDoS attack in network systems.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grant No. 61802097), and the Project of Qianjiang Talent (Grant No. QJD1802020).
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Li, M., Yang, X., Chen, Y., Bhuiyan, Z.A. (2019). Optimal Personalized DDoS Attacks Detection Strategy in Network Systems. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_26
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DOI: https://doi.org/10.1007/978-981-15-1304-6_26
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