Detecting and Defending Mechanism Against DDoS Attacks in Programmable Data Plane
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    Abstract:

    Traditional detection and defense mechanisms for distributed denial-of-service (DDoS) attacks require traffic mirroring, collection, and centralized remote analysis, which introduces extra performance overhead and fails to achieve real-time protection in high-performance networks. With the development of network devices such as programmable switches, the programmable data plane has emerged as a solid foundation for achieving high-performance DDoS attack detection. However, existing detection methods based on the programmable data plane cannot guarantee accuracy and are difficult to deploy directly in programmable switches (such as Intel Tofino) due to programming constraints. To this end, this paper proposes a programmable switch-based mechanism for detecting and defending against DDoS attacks. First, the mechanism uses the difference between the entropy of source and destination addresses to determine whether DDoS attacks occur. When DDoS attacks occur, a traffic filtration mechanism based on the difference in counts between source and destination address will defend against DDoS attacks in real time. Experimental results indicate that the proposed mechanism effectively identifies and defends against DDoS attacks. Compared with the benchmark method, the accuracy of this mechanism in window-level attack detection is increased by 17.75% on average, and the accuracy of packet-level attack filtration is increased by 3.7% on average.

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武文浩,张磊磊,潘恒,李恩晗,周建二,李振宇.可编程数据平面DDoS检测与防御机制.软件学报,2025,36(8):3831-3857

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History
  • Received:July 12,2022
  • Revised:May 10,2023
  • Adopted:
  • Online: December 31,2024
  • Published: August 06,2025
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