Attention Based Collaborative Source-Side DDoS Attack Detection 


Vol. 13,  No. 4, pp. 157-165, Apr.  2024
https://doi.org/10.3745/TKIPS.2024.13.4.157


PDF Full-Text
  Abstract

The evolution of the Distributed Denial of Service Attack(DDoS Attack) method has increased the difficulty in the detection process. One of the solutions to overcome the problems caused by the limitations of the existing victim-side detection method was the source-side detection technique. However, there was a problem of performance degradation due to network traffic irregularities. In order to solve this problem, research has been conducted to detect attacks using a collaborative network between several nodes based on artificial intelligence. Existing methods have shown limitations, especially in nonlinear traffic environments with high Burstness and jitter. To overcome this problem, this paper presents a collaborative source-side DDoS attack detection technique introduced with an attention mechanism. The proposed method aggregates detection results from multiple sources and assigns weights to each region, and through this, it is possible to effectively detect overall attacks and attacks in specific few areas. In particular, it shows a high detection rate with a low false positive of about 6% and a high detection rate of up to 4.3% in a nonlinear traffic dataset, and it can also confirm improvement in attack detection problems in a small number of regions compared to methods that showed limitations in the existing nonlinear traffic environment.

  Statistics
  Cite this article

[IEEE Style]

H. Kim, S. Jeong, K. Kim, "Attention Based Collaborative Source-Side DDoS Attack Detection," The Transactions of the Korea Information Processing Society, vol. 13, no. 4, pp. 157-165, 2024. DOI: https://doi.org/10.3745/TKIPS.2024.13.4.157.

[ACM Style]

Hwisoo Kim, Songheon Jeong, and Kyungbaek Kim. 2024. Attention Based Collaborative Source-Side DDoS Attack Detection. The Transactions of the Korea Information Processing Society, 13, 4, (2024), 157-165. DOI: https://doi.org/10.3745/TKIPS.2024.13.4.157.

Forms

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

Old Journals

Indexing

All publications of TKIPS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

TKIPS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

Related Journals