Random Neural Networks and Deep Learning for Attack Detection at the Edge

被引：3
|
作者：
Brun, Olivier [1 ]
Yin, Yonghua [2 ]
机构：
[1] Univ Toulouse, CNRS, LAAS, Toulouse, France
[2] Imperial Coll, Elect & Elect Engn Dept, Intelligent Syst & Networks Grp, London SW7 2AZ, England
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON FOG COMPUTING (ICFC 2019) | 2019年
基金：
欧盟地平线“2020”;
关键词：
Cybersecurity; IoT; attack detection; deep learning; dense random neural network; Fog Computing;
D O I：
10.1109/ICFC.2019.00009
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we analyze the network attacks that can be launched against Internet of Things (IoT) gateways, identify the relevant metrics to detect them, and explain how they can be computed from packet captures. We then present the principles and design of a deep learning-based approach using dense random neural networks (RNN) for the online detection of network attacks. Empirical validation results on packet captures in which attacks are inserted show that the Dense RNN correctly detects attacks.
引用
收藏
页码：11 / 14
页数：4
相关论文
共 50 条
  • [41] Transfer learning approach in deep neural networks for uterine fibroid detection
    Sundar, Sumod
    Sumathy, S.
    INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2022, 25 (01) : 52 - 63
  • [42] Deep Learning Poison Data Attack Detection
    Chacon, Henry
    Silva, Samuel Henrique
    Rad, Paul
    2019 IEEE 31ST INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2019), 2019, : 971 - 978
  • [43] Recommendation attack detection based on deep learning
    Zhou, Quanqiang
    Wu, Jinxia
    Duan, Liangliang
    JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2020, 52
  • [44] Deep Learning Based Cyber Attack Detection in 6G Wireless Networks
    Gupta, Brij B.
    Chui, Kwok Tai
    Gaurav, Akshat
    Arya, Varsha
    2023 IEEE 98TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-FALL, 2023,
  • [45] Deep Learning Approaches for DDoS Attack Detection in Communication Networks and IoT: A Comprehensive Review
    Abdulrahman, Nabeel Fouad
    Singh, Mandeep Singh Jit
    JURNAL KEJURUTERAAN, 2025, 37 (01): : 323 - 333
  • [46] QRS Complex Detection Using Novel Deep Learning Neural Networks
    Cai, Wenjie
    Hu, Danqin
    IEEE ACCESS, 2020, 8 : 97082 - 97089
  • [47] Deepfake Detection with Deep Learning: Convolutional Neural Networks versus Transformers
    Thing, Vrizlynn L. L.
    2023 IEEE INTERNATIONAL CONFERENCE ON CYBER SECURITY AND RESILIENCE, CSR, 2023, : 246 - 253
  • [48] Foam detection in a stirred tank using deep learning neural networks
    Hoseini, S. S.
    Rundquist, E.
    Poux, M.
    Aubin, J.
    CHEMICAL ENGINEERING RESEARCH & DESIGN, 2024, 209 : 346 - 357
  • [49] IoT Attack Detection with Deep Learning Analysis
    Pecori, Riccardo
    Tayebi, Amin
    Vannucci, Armando
    Veltri, Luca
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
  • [50] DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things
    Ahmad, Jawad
    Shah, Syed Aziz
    Latif, Shahid
    Ahmed, Fawad
    Zou, Zhuo
    Pitropakis, Nikolaos
    JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2022, 34 (10) : 8112 - 8121
12345