Skip to main navigation Skip to search Skip to main content

BlockDeepNet: A blockchain-based secure deep learning for IoT network

  • Seoul National University of Science and Technology (SNUST)
  • Georgia State University

Research output: Contribution to journalArticlepeer-review

88 Scopus citations

Abstract

The recent development in IoT and 5G translates into a significant growth of Big data in 5G-envisioned industrial automation. To support big data analysis, Deep Learning (DL) has been considered the most promising approach in recent years. Note, however, that designing an effective DL paradigm for IoT has certain challenges such as single point of failure, privacy leak of IoT devices, lack of valuable data for DL, and data poisoning attacks. To this end, we present BlockDeepNet, a Blockchain-based secure DL that combines DL and blockchain to support secure collaborative DL in IoT. In BlockDeepNet, collaborative DL is performed at the device level to overcome privacy leak and obtain enough data for DL, whereas blockchain is employed to ensure the confidentiality and integrity of collaborative DL in IoT. The experimental evaluation shows that BlockDeepNet can achieve higher accuracy for DL with acceptable latency and computational overhead of blockchain operation.

Original languageEnglish
Article number3974
JournalSustainability (Switzerland)
Volume11
Issue number14
DOIs
StatePublished - 1 Jul 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Blockchain
  • Collaborative deep learning
  • Deep learning
  • IoT
  • Security and privacy

Fingerprint

Dive into the research topics of 'BlockDeepNet: A blockchain-based secure deep learning for IoT network'. Together they form a unique fingerprint.

Cite this