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Abstract

One of the popular ways of attaching networks and servers is by adopting DDoS (Distributed denial of service). The preferred sector of hacking targeted are online services and networked area with high traffic. Although innovative and modern methods have been developed to mitigate these threats, there is still a need for more effective techniques to detect DDoS HTTP flooding attacks. This paper aims to address this gap by proposing an advanced mathematical approach capable of efficiently handling, processing, and detecting DDoS HTTP flooding attacks. The paper introduces a unique method based on the summation of rows and columns in a two-dimensional array representation of network traffic, offering a novel solution for detecting DDoS HTTP flooding attacks targeting web servers. The incoming traffic is first separated into aggregated packets based on time (t), and each aggregated packet is further divided into smaller time intervals called events. These events are then grouped based on time (t) into packets of equal size with the same inter-arrival time in which the proposed mechanism applied to detect DDoS HTTP flooding attacks. By carrying out detailed study about the experimental results on CIC DDoS dataset, an accuracy rate of 99.11% was re-ported. This indicates the effectiveness of detecting HTTP flooding DDoS attacks.

Keywords

DDoS attacks, HTTP flooding, Networking security, Online services, Quantitative metrics

Subject Area

Computer Science

Article Type

Article

First Page

2700

Last Page

2713

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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