Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Cyber Attacks Management in IoT Networks Using Deep Learning and Edge Computing

Published: 11 February 2025 Publication History

Abstract

This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cyberse-curity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT

References

[1]
A. Alwarafy, M. Abdallah, J. Schneider, M. Hamdi, ”A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet of Things” in IEEE Internet of Things Journal, DOI 10.1109/JIOT.2020.3015432.
[2]
A Nait Abbou., Y Baddi., A Hasbi., IoT Smart Home Ecosystem: Architecture and Communication Protocols, in: International Conference of Computer Science and Renewable Energies (ICCSRE), 2019,.
[3]
X. Yuan, C. Li, X. Li, DeepDefense: Identifying DDoS Attack via Deep Learning, in: 2017 IEEE International Conference on Smart Computing (SMARTCOMP), 2017, pp. 1–8.
[4]
A Nait Abbou., Y Baddi., A Hasbi, Wireless Sensor Networks as part of IOT: Performance study of WiMax - Mobil protocol, in: 4th International Conference on Cloud Computing Technologies and Applications (Cloudtech), 2018,.
[5]
Zemrane, H., Baddi, Y., Hasbi, ”Internet of Things Smart Home Ecosystem”. in Elhoseny, M., Hassanien, A. (eds) Emerging Technologies for Connected Internet of Vehicles and Intelligent Transportation System Networks. Studies in Systems, Decision and Control, vol 242. Springer, Cham., https://doi.org/10.1007/978-3-030-22773-98
[6]
K. Gref, R.K. Srivastava, J. Koutník, B.R. Steunebrink, J. Schmidhuber, LSTM: A search space odyssey, IEEE transactions on neural networks and learning systems 28 (2017) 2222–2232.
[7]
A. Abeshu, N. Chilamkurti, Deep learning: the frontier for distributed attack detection in Fog-to-Things computing, IEEE Communications Magazine 56 (2018) 169–175.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Procedia Computer Science
Procedia Computer Science  Volume 251, Issue C
2024
824 pages
ISSN:1877-0509
EISSN:1877-0509
Issue’s Table of Contents

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 11 February 2025

Author Tags

  1. Internet of Things (IoT)
  2. cybersecurity
  3. machine learning
  4. deep learning

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 13 Feb 2025

Other Metrics

Citations

View Options

View options

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media