Deep learning and blockchain-empowered security framework for intelligent 5G-enabled IoT

Shailendra Rathore, Jong Hyuk Park, Hangbae Chang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Recently, many IoT applications, such as smart transportation, healthcare, and virtual and augmented reality experiences, have emerged with fifth-generation (5G) technology to enhance the Quality of Service (QoS) and user experience. The revolution of 5G-enabled IoT supports distinct attributes, including lower latency, higher system capacity, high data rate, and energy saving. However, such revolution also delivers considerable increment in data generation that further leads to a major requirement of intelligent and effective data analytic operation across the network. Furthermore, data growth gives rise to data security and privacy concerns, such as breach and loss of sensitive data. The conventional data analytic and security methods do not meet the requirement of 5G-enabled IoT including its unique characteristic of low latency and high throughput. In this paper, we propose a Deep Learning (DL) and blockchain-empowered security framework for intelligent 5G-enabled IoT that leverages DL competency for intelligent data analysis operation and blockchain for data security. The framework's hierarchical architecture wherein DL and blockchain operations emerge across the four layers of cloud, fog, edge, and user is presented. The framework is simulated and analyzed, employing various standard measures of latency, accuracy, and security to demonstrate its validity in practical applications.

Original languageEnglish
Pages (from-to)90075-90083
Number of pages9
JournalIEEE Access
Volume9
Early online date3 May 2021
DOIs
Publication statusPublished - 3 May 2021
Externally publishedYes

Keywords

  • Internet of Things
  • Security attack detection
  • Edge computing
  • Fog computing
  • Blockchain
  • Software-defined networking

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