Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey
Author:
Affiliation:
1. School of Computer Science, The University of Auckland, Auckland, New Zealand
2. Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/9739/10051138/10005100.pdf?arnumber=10005100
Reference166 articles.
1. Statistical analysis of honeypot data and building of Kyoto 2006+ dataset for NIDS evaluation
2. A detailed analysis of the KDD CUP 99 data set
3. An empirical comparison of botnet detection methods
4. Toward developing a systematic approach to generate benchmark datasets for intrusion detection
5. Deep Learning Models for Cyber Security in IoT Networks
Cited by 80 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. Optimisation of multiple clustering based undersampling using artificial bee colony: Application to improved detection of obfuscated patterns without adversarial training;Information Sciences;2025-01
2. NIDS-Vis: Improving the generalized adversarial robustness of network intrusion detection system;Computers & Security;2024-10
3. Real-time fusion multi-tier DNN-based collaborative IDPS with complementary features for secure UAV-enabled 6G networks;Expert Systems with Applications;2024-10
4. A Complete EDA and DL Pipeline for Softwarized 5G Network Intrusion Detection;Future Internet;2024-09-10
5. A sequential deep learning framework for a robust and resilient network intrusion detection system;Computers & Security;2024-09
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