Od-ids2022: generating a new offensive defensive intrusion detection dataset for machine learning-based attack classification

Author:

Patel N. D.ORCID,Mehtre B. M.,Wankar Rajeev

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Reference95 articles.

1. Hettich S (1999) Kdd cup 1999 data. The UCI KDD Archive

2. Tavallaee M, Bagheri E, Lu W, Ghorbani A (2009) A detailed analysis of the KDD CUP 99 data set. 2009 IEEE symposium on computational intelligence for security and defense applications. pp. 1-6

3. Revathi S, Malathi A (2013) A detailed analysis on NSL-KDD dataset using various machine learning techniques for intrusion detection. Int J Eng Res Technol (IJERT) 2:1848–1853

4. Moustafa N, Slay J (2015) UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set). 2015 military communications and information systems conference (MilCIS). pp. 1-6

5. Panigrahi R, Borah S (2018) A detailed analysis of CICIDS2017 dataset for designing intrusion detection systems. Int J Eng Res Technol 7:479–482

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. SEDAT: A Stacked Ensemble Learning-Based Detection Model for Multiscale Network Attacks;Electronics;2024-07-26

2. Deep Learning-Based Methodology for Tracking Cybersecurity in Networked Computers;Advances in IT Standards and Standardization Research;2024-05-31

3. ChOs_LSTM: Chebyshev Osprey Optimization-Based Model for Detecting Attacks;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03

4. Enhancing intrusion detection using coati optimization algorithm with deep learning on vehicular Adhoc networks;International Journal of Information Technology;2024-04-10

5. Intrusion Detection Techniques in Internet of Things: A Bird’s Eye View;2024 11th International Conference on Computing for Sustainable Global Development (INDIACom);2024-02-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3