Related references
Note: Only part of the references are listed.Nearest cluster-based intrusion detection through convolutional neural networks
Giuseppina Andresini et al.
KNOWLEDGE-BASED SYSTEMS (2021)
Hybrid Deep Learning for Botnet Attack Detection in the Internet-of-Things Networks
Segun Popoola et al.
IEEE INTERNET OF THINGS JOURNAL (2021)
Hybrid approach to intrusion detection in fog-based IoT environments
Cristiano Antonio de Souza et al.
COMPUTER NETWORKS (2020)
Distributed Learning for Automatic Modulation Classification in Edge Devices
Yu Wang et al.
IEEE WIRELESS COMMUNICATIONS LETTERS (2020)
6G: Opening New Horizons for Integration of Comfort, Security, and Intelligence
Guan Gui et al.
IEEE WIRELESS COMMUNICATIONS (2020)
Hybrid Intrusion Detection System for Edge-Based IIoT Relying on Machine-Learning-Aided Detection
Haipeng Yao et al.
IEEE NETWORK (2019)
Attacker Identification and Intrusion Detection for In-Vehicle Networks
Jing Ning et al.
IEEE COMMUNICATIONS LETTERS (2019)
Host-Based Intrusion Detection System with System Calls: Review and Future Trends
Ming Liu et al.
ACM COMPUTING SURVEYS (2019)
A Novel Multimodal-Sequential Approach Based on Multi-View Features for Network Intrusion Detection
Haitao He et al.
IEEE ACCESS (2019)
Deep Learning Approach for Intelligent Intrusion Detection System
R. Vinayakumar et al.
IEEE ACCESS (2019)
Novel Geometric Area Analysis Technique for Anomaly Detection Using Trapezoidal Area Estimation on Large-Scale Networks
Nour Moustafa et al.
IEEE TRANSACTIONS ON BIG DATA (2019)
Deep Abstraction and Weighted Feature Selection for Wi-Fi Impersonation Detection
Muhamad Erza Aminanto et al.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2018)
Leveraging LSTM Networks for Attack Detection in Fog-to-Things Communications
Abebe Diro et al.
IEEE COMMUNICATIONS MAGAZINE (2018)
Energy-Efficient Intrusion Detection with a Barrier of Probabilistic Sensors: Global and Local
Jiming Chen et al.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2013)
Share Paper
