Bolstering IoT security with IoT device type Identification using optimized Variational Autoencoder Wasserstein Generative Adversarial Network-Reference-Cited by-同舟云学术

Bolstering IoT security with IoT device type Identification using optimized Variational Autoencoder Wasserstein Generative Adversarial Network

Published:2024-01-31 Issue:3 Volume:35 Page:278-299
ISSN:0954-898X
Container-title:Network: Computation in Neural Systems
language:en
Short-container-title:Network: Computation in Neural Systems

Author:

Sankar Jothi Shri¹,Dhatchnamurthy Saravanan²,X Anitha Mary³,Gupta Keerat Kumar⁴

Affiliation:

1. Department of Computer Science and Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India

2. Assistant Professor, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India

3. Department of Robotics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India

4. Department of Civil Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India

Funder

no funding associated with the work featured

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0954898X.2024.2304214

Reference24 articles.

1. Deep learning-enabled anomaly detection for IoT systems

2. Developing Hybrid Demand Response Technique for Energy Management in Microgrid Based on Pelican Optimization Algorithm

3. Ali S, Abusabha O, Ali F, Imran M, ABUHMED T. 2022. Effective multitask deep learning for iot malware detection and identification using behavioral traffic analysis. In IEEE Transactions on Network and Service Management.

4. CAM-YOLO: tomato detection and classification based on improved YOLOv5 using combining attention mechanism

5. A holistic IoT device classification approach through spatial & temporal behaviors modelling