A review of technique to self-generate DDoS dataset

Application Layer Distributed Denial of Service (DDoS) attacks are very challenging to detect and the most common and renowned application layer attack is HTTP flooding. There several approaches adopted by past studies to acquire the dataset such publicly download from and Internet and self-generate...

Full description

Saved in:
Bibliographic Details
Main Authors: Jaafar, G. A., Abdullah, S. M., Adli, S.
Format: Article
Published: World Academy of Research in Science and Engineering 2019
Subjects:
Online Access:http://eprints.utm.my/id/eprint/90649/
http://dx.doi.org/10.30534/ijatcse/2019/88842019
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.90649
record_format eprints
spelling my.utm.906492021-04-29T23:28:19Z http://eprints.utm.my/id/eprint/90649/ A review of technique to self-generate DDoS dataset Jaafar, G. A. Abdullah, S. M. Adli, S. T Technology (General) Application Layer Distributed Denial of Service (DDoS) attacks are very challenging to detect and the most common and renowned application layer attack is HTTP flooding. There several approaches adopted by past studies to acquire the dataset such publicly download from and Internet and self-generate by utilizing attack script. Use of old dataset should be prevented as it led to meaningless result. The current available application layer DDoS dataset is obsolete. Furthermore, the latest dataset is not publicly available due to security issue. Hence, DDoS researchers have to move to other atmosphere in order to obtain the latest dataset for DDoS attack execute at application layer. A few attack scripts publicly available which allow researcher to utilize. The attack script requires to work together with actual devices such as a set of computers, web server and other related network devices to create experimental lab. Execution of the attack script also need to pay attention as different attack script utilize different command to run. This paper reviewed 12 techniques utilize by prior studies to self-generate dataset. A summary of each technique is summarized in table view, along with in-depth critical analysis, for future studies to self-generate dataset in conducting DDoS experiment. World Academy of Research in Science and Engineering 2019-07 Article PeerReviewed Jaafar, G. A. and Abdullah, S. M. and Adli, S. (2019) A review of technique to self-generate DDoS dataset. International Journal of Advanced Trends in Computer Science and Engineering, 8 (4). pp. 1630-1638. ISSN 2278-3091 http://dx.doi.org/10.30534/ijatcse/2019/88842019 DOI: 10.30534/ijatcse/2019/88842019
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Jaafar, G. A.
Abdullah, S. M.
Adli, S.
A review of technique to self-generate DDoS dataset
description Application Layer Distributed Denial of Service (DDoS) attacks are very challenging to detect and the most common and renowned application layer attack is HTTP flooding. There several approaches adopted by past studies to acquire the dataset such publicly download from and Internet and self-generate by utilizing attack script. Use of old dataset should be prevented as it led to meaningless result. The current available application layer DDoS dataset is obsolete. Furthermore, the latest dataset is not publicly available due to security issue. Hence, DDoS researchers have to move to other atmosphere in order to obtain the latest dataset for DDoS attack execute at application layer. A few attack scripts publicly available which allow researcher to utilize. The attack script requires to work together with actual devices such as a set of computers, web server and other related network devices to create experimental lab. Execution of the attack script also need to pay attention as different attack script utilize different command to run. This paper reviewed 12 techniques utilize by prior studies to self-generate dataset. A summary of each technique is summarized in table view, along with in-depth critical analysis, for future studies to self-generate dataset in conducting DDoS experiment.
format Article
author Jaafar, G. A.
Abdullah, S. M.
Adli, S.
author_facet Jaafar, G. A.
Abdullah, S. M.
Adli, S.
author_sort Jaafar, G. A.
title A review of technique to self-generate DDoS dataset
title_short A review of technique to self-generate DDoS dataset
title_full A review of technique to self-generate DDoS dataset
title_fullStr A review of technique to self-generate DDoS dataset
title_full_unstemmed A review of technique to self-generate DDoS dataset
title_sort review of technique to self-generate ddos dataset
publisher World Academy of Research in Science and Engineering
publishDate 2019
url http://eprints.utm.my/id/eprint/90649/
http://dx.doi.org/10.30534/ijatcse/2019/88842019
_version_ 1698696965817106432
score 13.214268