A Lightweight DNN-based IDS for Detecting IoT Cyberattacks in Edge Computing
Author:
Affiliation:
1. Posts and Telecommunications Institute of Technology,Telecommunication Faculty Nol,Viet Nam
2. Thang Long University,Mathematics and Informatics Faculty,Ha Noi,Viet Nam
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9942959/9942960/09943049.pdf?arnumber=9943049
Reference17 articles.
1. IMPACT: Impersonation Attack Detection via Edge Computing Using Deep Autoencoder and Feature Abstraction
2. Design and Development of a Deep Learning-Based Model for Anomaly Detection in IoT Networks
3. Passban IDS: An Intelligent Anomaly-Based Intrusion Detection System for IoT Edge Devices
4. Intrusion detection system for iot botnet attacks using deep learning;shareena;SN Computer Science,2021
5. Realguard: A Lightweight Network Intrusion Detection System for IoT Gateways
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1. Machine Learning and Deep Learning Techniques for Internet of Things Network Anomaly Detection—Current Research Trends;Sensors;2024-03-20
2. A Novel DNN-Based IDS System Combined with an LR-GA Method to Detect Attacks;Lecture Notes in Networks and Systems;2024
3. Research and Implementation of Intelligent Learning Desk Based on Visio Sensor in AI IoT Environments for Smart Education;Sensors and Materials;2023-12-26
4. ML-Augmented Network Packet Broker based Anomaly Detection at IIoT-Edge Egress Port;2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS);2023-12-17
5. RSM: A Real-time Security Monitoring Platform for IoT Networks;2023 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2023-09-24
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