Intrusion Detection Based on Convolutional Neural Network in Complex Network Environment
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-15-0187-6_26
Reference10 articles.
1. Almseidin M, Alzubi M, Kovacs S et al (2017) Evaluation of machine learning algorithms for intrusion detection system. In: 15th IEEE international symposium on intelligent systems and informatics. IEEE, pp 277–282
2. Amudha P, Karthik S, Sivakumari S (2014) Classification techniques for intrusion detection-an overview. Int J Comput Appl 76(16):33–40
3. Godin F, Degrave J, Dambre J, De Neve W (2018) Dual rectified linear units (DReLUs): a replacement for Tanh activation functions in quasi-recurrent neural networks. Pattern Recogn Lett 116:8–14
4. Samrin R, Vasumathi D (2018) Hybrid weighted K-means clustering and artificial neural network for an anomaly-based network intrusion detection system. J Intell Syst 27(2):135–147
5. Divyasree TH, Sherly KK (2018) A network intrusion detection system based on ensemble CVM using efficient feature selection approach. Procedia Comput Sci 143:442–449
Cited by 5 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. NIDS-CNNLSTM: Network Intrusion Detection Classification Model Based on Deep Learning;IEEE Access;2023
2. Research on Intrusion Detection Algorithm Based on Optimized CNN-LSTM;2022 International Conference on Networking and Network Applications (NaNA);2022-12
3. Withdraw article: A Survey on Network Intrusion Detection using Convolutional Neural Network;ITM Web of Conferences;2022
4. A Survey on Network Intrusion Detection using Convolutional Neural Network;ITM Web of Conferences;2022
5. Intelligent analysis framework for healthy environment spatial model of BIM horticultural therapy based on complex network information model;Soft Computing;2020-07-17
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