LGTBIDS: Layer-Wise Graph Theory-Based Intrusion Detection System in Beyond 5G-Reference-Cited by-同舟云学术

LGTBIDS: Layer-Wise Graph Theory-Based Intrusion Detection System in Beyond 5G

Published:2023-03 Issue:1 Volume:20 Page:658-671
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Shafi Misbah¹,Jha Rakesh Kumar²^ORCID,Jain Sanjeev³^ORCID

Affiliation:

1. Department of Electronics and Communication, Shri Mata Vaishno Devi University, Katra, India

2. Department of Electronics and Communication Engineering, Indian Institute of Information Technology Design and Manufacturing Jabalpur, Jabalpur, India

3. Department of Computer Science and Engineering, Central University of Jammu, Jammu, India

Funder

IIITDM

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/4275028/10065607/09854879.pdf?arnumber=9854879

Reference31 articles.

1. AI-Based Two-Stage Intrusion Detection for Software Defined IoT Networks

2. On the Feasibility of Deep Learning in Sensor Network Intrusion Detection

3. Leveraging LSTM Networks for Attack Detection in Fog-to-Things Communications

4. Implementation of Intrusion Detection System using Adaptive Neuro-Fuzzy Inference System for 5G wireless communication network

5. Behavioral Model for Live Detection of Apps Based Attack

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2. Robust Deep Regressive Neural Learning Based Intrusion Detection and Prevention in Wireless Communication;2023 International Conference on Emerging Research in Computational Science (ICERCS);2023-12-07

3. DeepFedKDAD: Deep Federated Knowledge Distillation Based Anomaly Detection in B5G Network Slicing;2023 International Conference on Networks, Communications and Intelligent Computing (NCIC);2023-11-17