A Novel Deep Hierarchical Machine Learning Approach for Identification of Known and Unknown Multiple Security Attacks in a D2D Communications Network-Reference-Cited by-同舟云学术

A Novel Deep Hierarchical Machine Learning Approach for Identification of Known and Unknown Multiple Security Attacks in a D2D Communications Network

Published:2023 Issue: Volume:11 Page:95161-95194
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rani S. V. Jansi¹^ORCID,Ioannou Iacovos I.²^ORCID,Nagaradjane Prabagarane³,Christophorou Christophoros²^ORCID,Vassiliou Vasos²,Yarramsetti Harshitaa¹^ORCID,Shridhar Sai¹,Balaji L. Mukund¹^ORCID,Pitsillides Andreas²^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India

2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

3. Department of ECE, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India

Funder

European Union’fs Horizon 2020 Research and Innovation Program

Government of the Republic of Cyprus through the Directorate General for European Programs, Coordination, and Development

European Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10227259.pdf?arnumber=10227259

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2. A taxonomy and comparison of computer security incidents from the commercial and government sectors

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4. Detection of DDoS attacks in D2D communications using machine learning approach

5. Developing Realistic Distributed Denial of Service (DDoS) Attack Dataset and Taxonomy

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