Heuristic Rules for Attack Detection Charged by NSL KDD Dataset

Author:

Wutyi Khaing Shwe,Thwin Mie Mie Su

Publisher

Springer International Publishing

Reference24 articles.

1. Agarwal, R., Joshi, M.V.: PNrule: A New Framework for Learning Classifier Models in Data Mining (A Case-Study in Network Intrusion Detection). Technical Report TR 00-015, Department of Computer Science, University of Minnesota (2000)

2. Levin, I.: KDD-99 Classifier Learning Contest LLSoft’s Results Overview. ACM SIGKDD SIGKDD Explorations 1(2), 67–75 (2000)

3. Lee, W., Stolfo, S.J., Mok, K.W.: A data mining framework for building intrusion detection models. In: IEEE Symposium on Security and Privacy, Oakland, California, pp. 120–132 (1999)

4. Lindqvist, U., Porras, P.: Detecting computer and network misuse through the production-based expert system toolset (P-{BEST}). In: IEEE Symposium on Security and Privacy, pp. 146–161 (1999)

5. Porras, P.A., Neumann, P.G.: EMERALD: event monitoring enabling responses to anomalous live disturbances. In: Proceedings of the 20th National Information Systems Security Conference, Baltimore, Maryland, pp. 353–365 (1997)

Cited by 7 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. Advancements of Machine Learning in Malware and Intrusion Detections;2024 International Conference on Computer, Information and Telecommunication Systems (CITS);2024-07-17

2. IDC-insight: boosting intrusion detection accuracy in IoT networks with Naïve Bayes and multiple classifiers;International Journal of Information Technology;2024-06-24

3. i-2NIDS Novel Intelligent Intrusion Detection Approach for a Strong Network Security;International Journal of Information Security and Privacy;2023-02-03

4. The impact of Under-Sampling Techniques on Classification Accuracy in multi-class Imbalance Data;2022 3rd International Conference on Electrical Engineering and Informatics (ICon EEI);2022-10-19

5. Intrusion Detection using Nature‐Inspired Algorithms and Automated Machine Learning;Smart and Sustainable Intelligent Systems;2021-03-24

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