Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection

Рахматов, Ф.А., Холмуминов, О.Т.

Рақамли технологияларнинг назарий ва амалий масалалари · 2025-yil

Annotatsiya

To effectively detect and prevent DDoS (Distributed Denial-of-Service) attacks, it is necessary to use various datasets. This article analyzes the most popular datasets for DDoS attack detection, including CIC-DDoS2019, NSL-KDD, UNSW-NB15, BoT-IoT, and CAIDA, evaluating their performance metrics. Each dataset is assessed based on attack types, size, real-time proximity, and usability. Furthermore, the accuracy and F1-score metrics of machine learning models on these datasets are compared. The results indicate that the CIC-DDoS2019 dataset is the most comprehensive and close to real-world scenarios, providing high performance with Random Forest and SVM algorithms. The study guides in selecting the optimal dataset and model combination for DDoS attack detection.

Maqola ma’lumotlari
MualliflarРахматов, Ф.А., Холмуминов, О.Т.
JurnalРақамли технологияларнинг назарий ва амалий масалалари
NashriyotТАТУ Самарқанд филиали
ISSN2181-3086, 2181-3094
Nashr sanasi2025-09-20
Jild8
Son3
Betlar94-100
TilIngliz
Ilmiy sohaTexnika
DOI10.62132/ijdt.v8i3.292
Indeksga qo‘shilgan2026-08-26

DOI: 10.62132/ijdt.v8i3.292 · Maqolaning asl sahifasi

Kalit so‘zlar

набор данных, машинное обучение, DDoS, CIC-DDoS2019, KNN, Random Forest, SVM, SYN Flood, UDP Flood, HTTP Flood, dataset, machine learning, DDoS, CIC-DDoS2019, KNN, Random Forest, SVM, SYN Flood, UDP Flood, HTTP Flood

Ilmiy soha

Texnika

Iqtibos keltirish

APAРахматов, Ф.А., & Холмуминов, О.Т. (2025). Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection. Рақамли технологияларнинг назарий ва амалий масалалари, 8(3), 94-100. https://doi.org/10.62132/ijdt.v8i3.292
GOST (OAK)Рахматов, Ф.А., Холмуминов, О.Т. Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection // Рақамли технологияларнинг назарий ва амалий масалалари. – 2025. – T. 8, № 3. – P. 94-100. – DOI: 10.62132/ijdt.v8i3.292.
MLAРахматов, Ф.А., and Холмуминов, О.Т. “Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection.” Рақамли технологияларнинг назарий ва амалий масалалари, 8(3), 94-100, 2025. https://doi.org/10.62132/ijdt.v8i3.292
ChicagoРахматов, Ф.А., and Холмуминов, О.Т. “Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection.” Рақамли технологияларнинг назарий ва амалий масалалари, 8(3), 94-100 (2025). https://doi.org/10.62132/ijdt.v8i3.292
HarvardРахматов, Ф.А., and Холмуминов, О.Т (2025) ‘Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection’, Рақамли технологияларнинг назарий ва амалий масалалари, 8(3), 94-100. https://doi.org/10.62132/ijdt.v8i3.292
BibTeX
@article{article2025,
  title = {Analysis of the Performance Metrics of Existing Datasets for DDoS Attack Detection},
  author = {Рахматов, Ф.А. and Холмуминов, О.Т.},
  journal = {Рақамли технологияларнинг назарий ва амалий масалалари},
  year = {2025},
  volume = {8},
  number = {3},
  pages = {94-100},
  doi = {10.62132/ijdt.v8i3.292},
  url = {https://doi.org/10.62132/ijdt.v8i3.292}
}

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