Preventing DDoS using Bloom Filter: A Survey

TL;DR

This survey reviews how Bloom Filters, a probabilistic data structure, are used to defend against DDoS attacks by efficiently storing packet information with minimal memory.

Contribution

It provides a comprehensive overview of the deployment of Bloom Filters in DDoS defense mechanisms, highlighting their advantages and challenges.

Findings

Bloom Filters enable efficient DDoS detection with low memory usage.

They offer probabilistic membership queries to identify malicious traffic.

The survey discusses various implementations and future directions.

Abstract

Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.