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29 ta ish

Ish: Hybrid Deep Learning for Intrusion Detection in IoT Networks Using CNNs, Bigrus, Attention Mechanisms, and Advanced Binary Snake Optimizer (BSO) Techniques

  1. Securing IoT devices with zero day intrusion detection system using binary snake optimization and attention based bidirectional gated recurrent classifier

    Ali Saeed Almuflih, Ilyоs Abdullayev, Sergey Bakhvalov +4

    MaqolaNetwork Security and Intrusion DetectionScientific Reports20249 iqtibos
    ABI

  2. Network Intrusion Detection for IoT Security Based on Learning Techniques

    Nadia Chaabouni, Mohamed Mosbah, Akka Zemmari +2

    Maqola20193 iqtibos
    ABI

  3. Empirical Analysis of Data Streaming and Batch Learning Models for Network Intrusion Detection

    Kayode S. Adewole, Taofeekat Tosin Salau-Ibrahim, Agbotiname Lucky Imoize +6

    Maqola20222 iqtibos
    ABI

  4. Machine learning and deep learning methods for intrusion detection systems: recent developments and challenges

    Geeta Kocher, Gulshan Kumar

    Maqola20212 iqtibos
    ABI

  5. Composition of Hybrid Deep Learning Model and Feature Optimization for Intrusion Detection System

    Azriel Henry, Sunil Gautam, Samrat Khanna +5

    Maqola20232 iqtibos
    ABI

  6. A novel hybrid ensemble learning for anomaly detection in industrial sensor networks and SCADA systems for smart city infrastructures

    Yakub Kayode Saheed, Oluwadamilare Harazeem Abdulganiyu, Taha Ait Tchakoucht

    Maqola20232 iqtibos
    ABI

  7. A hybrid CNN-LSTM approach for intelligent cyber intrusion detection system

    Sukhvinder Singh Bamber, Aditya Vardhan Reddy Katkuri, S. C. Sharma +1

    Maqola20242 iqtibos
    ABI

  8. A New Ensemble-Based Intrusion Detection System for Internet of Things

    Adeel Abbas, Muazzam A. Khan, Shahid Latif +3

    Maqola20212 iqtibos
    ABI

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