Research on the reliability of bloom filters to defend a distributed denial-of-service
Jiaran Liu · Applied and Computational Engineering · 2023
Distributed denial of service (DDoS) attacks are one of the threats to network security, and reasonable means of defense are sought. Bloom filter is a commonly used detection method, the research have listed different attacks in the paper and made it possible to compare it with other detection methods by analyzing how Bloom filter works. The research shows that the Bloom filter works by comparing the element to be queried with an already stored vector. If the query result is zero then the element does not exist, if it is one then it means that in most cases the element exists, but false positives are not excluded causing the element to be judged as existing. In this paper, the comparison with other methods also needs focus, the time complexity of inserting, searching, and deleting data is an important feature to consider when Bloom filters outperform other methods. The research also shows that the Bloom filter is to some extent better than other detection methods in terms of insertion, search, and deletion time. At the same time, the research showed that the use of Bloom filters in response to DDoS attacks is also very impressive, for the detection of link flooding attacks and the detection and processing speed of packets is commendable, can take up less memory to achieve better results.