Abstract
In recent years, with the continuous development of DDoS attacks, DDoS attacks are becoming easier to implement. More and more servers and even personal computers are under the threat of DDoS attacks, especially DDoS flood attacks. Its main purpose is to cause the target host’s TCP/IP protocol layer to become congested. In this paper, we propose a real-time visualization defense framework for DDoS attack. Our framework is based on spark-streaming so that it allows for parallel and distributed traffic analysis that can be deployed at high speed network links. Moreover, this framework includes a cylindrical coordinates Visualization Model, which enables users to recognize DDoS threats promptly and clearly. The experiments show that our framework is able to detect and visualize DDoS flooding attacks timely and efficiently.
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Acknowledgments
This work is partially supported by the Planned Science and Technology Project of Hunan Province, China (NO.2015JC3044), the National Natural Science Foundation of China (NO.61272147), and the National Science Fund for Young Scholars (NO.61309009).
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Jin, Y., Liang, Q., Zhang, J., Jin, O. (2017). A Real-Time Visualization Defense Framework for DDoS Attack. In: Zou, B., Li, M., Wang, H., Song, X., Xie, W., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-6385-5_29
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DOI: https://doi.org/10.1007/978-981-10-6385-5_29
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