Malicious Attack Detection in IoT by Generative Adversarial Networks

Srikanth Bethu

doi:10.1007/s42979-025-03874-w

ScienceGate Book Chapters

JOURNAL ARTICLE

Malicious Attack Detection in IoT by Generative Adversarial Networks

Srikanth Bethu

Year: 2025 Journal: SN Computer Science Vol: 6 (4) Publisher: Springer Nature

DOI: 10.1007/s42979-025-03874-w

Get Full-Text PDF Get Analytical Report

Keywords:

Adversarial system Generative grammar Computer science Computer security Generative adversarial network Internet of Things Artificial intelligence Deep learning

Metrics

Cited By

15.50

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Advanced Malware Detection Techniques

Physical Sciences → Computer Science → Signal Processing

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Malicious Attack Detection in IoT by Generative Adversarial Networks

Metrics

Citation History

Topics

Related Documents

Effective Malicious URL Detection by Using Generative Adversarial Networks

Generating and Detection Malicious URL Based on Generative Adversarial Networks

Increasing Detection Rate for Imbalanced Malicious Traffic using Generative Adversarial Networks

IDS-GAN: Adversarial Attack against Intrusion Detection Based on Generative Adversarial Networks

Defending Against Adversarial Attack Through Generative Adversarial Networks