NFDLM: A Lightweight Network Flow based Deep Learning Model for DDoS Attack Detection in IoT Domains

Author:

Saurabh Kumar1,Kumar Tanuj1,Singh Uphar1,Vyas O.P.1,Khondoker Rahamatullah2

Affiliation:

1. Indian Institute of Information Technology,Allahabad,India

2. THM University of Applied Sciences,Department of Business Informatics,Friedberg,Germany

Publisher

IEEE

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. HMS-IDS: Threat Intelligence Integration for Zero-Day Exploits and Advanced Persistent Threats in IIoT;Arabian Journal for Science and Engineering;2024-07-10

2. TMAP: A Threat Modeling and Attack Path Analysis Framework for Industrial IoT Systems (A Case Study of IoM and IoP);Arabian Journal for Science and Engineering;2024-06-18

3. Impact of Latent Space Dimension on IoT Botnet Detection Performance: VAE-Encoder Versus ViT-Encoder;2024 3rd International Conference for Innovation in Technology (INOCON);2024-03-01

4. Deep Learning Method for Detecting and Mitigating Distributed Denial of Service Attacks with Imbalanced Data;2024 International Conference on Integrated Circuits and Communication Systems (ICICACS);2024-02-23

5. A critical review of feature selection methods for machine learning in IoT security;International Journal of Communication Networks and Distributed Systems;2024

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