| Title | Research on DDoS Attack Detection based on Multi-dimensional Entropy |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Zhou, Yansen, Chen, Qi, Wang, Yumiao |
| Conference Name | 2021 IEEE 9th International Conference on Computer Science and Network Technology (ICCSNT) |
| Keywords | Computer science, Conferences, DDoS attack detection, denial-of-service attack, detection algorithms, Dimension detection, distributed denial of service, Entropy, Human Behavior, information entropy, Metrics, pubcrawl, resilience, Resiliency, threshold, Time complexity |
| Abstract | DDoS attack detection in a single dimension cannot cope with complex and new attacks. Aiming at the problems existing in single dimension detection, this paper proposes an algorithm to detect DDoS attack based on multi-dimensional entropy. Firstly, the algorithm selects multiple dimensions and establishes corresponding decision function for each dimension and calculates its information entropy. Secondly, the multidimensional sliding window CUSUM algorithm without parameters is used to synthesize the detection results of three dimensions to determine whether it is attacked by DDoS. Finally, the data set published by MIT Lincoln Laboratory is used for testing. Experimental results show that compared with single dimension detection algorithm, this method has good detection rate and low false alarm rate. |
| DOI | 10.1109/ICCSNT53786.2021.9615450 |
| Citation Key | zhou_research_2021 |
Research on DDoS Attack Detection based on Multi-dimensional Entropy