Hybrid approach with Deep Auto-Encoder and optimized LSTM based Deep Learning approach to detect anomaly in cloud logs

被引:0
|
作者
Pankajashan, Savaridassan [1 ]
Maragatham, G. [1 ]
Kirthiga Devi, T. [1 ]
机构
[1] Department of Information Technology, SRM Institute of Science and Technology, Kattankualathur, Chennai, Tami Nadu, India
来源
关键词
461.1 Biomedical Engineering - 461.4 Ergonomics and Human Factors Engineering - 716.1 Information Theory and Signal Processing - 722.4 Digital Computers and Systems - 723 Computer Software; Data Handling and Applications - 821.0 Woodlands and Forestry - 903.1 Information Sources and Analysis;
D O I
暂无
中图分类号
学科分类号
摘要
32
引用
收藏
页码:6257 / 6271
相关论文
共 50 条
  • [1] Hybrid approach with Deep Auto-Encoder and optimized LSTM based Deep Learning approach to detect anomaly in cloud logs
    Pankajashan, Savaridassan
    Maragatham, G.
    Devi, T. Kirthiga
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 42 (06) : 6257 - 6271
  • [2] A Novel Deep Learning Approach: Stacked Evolutionary Auto-encoder
    Cai, Yaoming
    Cai, Zhihua
    Zeng, Meng
    Liu, Xiaobo
    Wu, Jia
    Wang, Guangjun
    2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2018,
  • [3] A Deep Learning Method Based on Hybrid Auto-Encoder Model
    Yang, ZhenYu
    Jing, Hui
    PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC), 2017, : 1100 - 1104
  • [4] A Deep Auto-Encoder based Approach for Intrusion Detection System
    Farahnakian, Fahimeh
    Heikkonen, Jukka
    2018 20TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT), 2018, : 178 - 183
  • [5] Online deep learning based on auto-encoder
    Zhang, Si-si
    Liu, Jian-wei
    Zuo, Xin
    Lu, Run-kun
    Lian, Si-ming
    APPLIED INTELLIGENCE, 2021, 51 (08) : 5420 - 5439
  • [6] Online deep learning based on auto-encoder
    Si-si Zhang
    Jian-wei Liu
    Xin Zuo
    Run-kun Lu
    Si-ming Lian
    Applied Intelligence, 2021, 51 : 5420 - 5439
  • [7] Unsupervised Deep Spectrum Sensing: A Variational Auto-Encoder Based Approach
    Xie, Jiandong
    Fang, Jun
    Liu, Chang
    Yang, Linxiao
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (05) : 5307 - 5319
  • [8] Unsupervised deep learning approach using a deep auto-encoder with an one-class support vector machine to detect structural damage
    Wang, Zilong
    Cha, Young-Jin
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2021, 20 (01): : 406 - 425
  • [9] Deep auto-encoder based clustering
    Song, Chunfeng
    Huang, Yongzhen
    Liu, Feng
    Wang, Zhenyu
    Wang, Liang
    INTELLIGENT DATA ANALYSIS, 2014, 18 : S65 - S76
  • [10] A re-optimized deep auto-encoder for gas turbine unsupervised anomaly detection
    Fu, Song
    Zhong, Shisheng
    Lin, Lin
    Zhao, Minghang
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2021, 101