Sustainable Secure Management against APT Attacks for Intelligent Embedded-Enabled Smart Manufacturing

Jun Wu, Mianxiong Dong*, Kaoru Ota, Jianhua Li, Wu Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Intelligent embedded-enable smart manufacturing is an important infrastructure for future industries. Increasing security threats are disturbing the normal operations of smart manufacturing. As a novel type of threat, an advanced persistent threat (APT) has the novel features of strong concealment, latency, and long-term entanglement, which can penetrate the core systems of smart manufacturing, especially for intelligent embedded systems, and cause great destruction from the cyber side to physical side. However, the existing security schemes cannot provide sustainable resource management, which causes the core system in smart manufacturing not to perform sustainable secure detection and defense against APTs. To address this challenge, this paper proposes a sustainable secure management mechanism for smart manufacturing against APTs. The proposed mechanism includes two parts: sustainable threat intelligence analysis and sustainable secure resource management. Sustainable threat intelligence analysis provides sustainable discovery of the indications of potential APTs, which has features of a weak signal, low correlation, and slow time variation. The sustainable secure resource management provides deep and continuous protection for intelligent embedded systems in smart manufacturing. The evaluations show the defense capabilities and the feasibility of the proposed mechanism.

Original languageEnglish
Article number8698833
Pages (from-to)341-352
Number of pages12
JournalIEEE Transactions on Sustainable Computing
Issue number3
Publication statusPublished - 2020 Jul 1
Externally publishedYes


  • Smart manufacturing
  • advanced persistent threat (APT)
  • resource management
  • sustainable security

ASJC Scopus subject areas

  • Software
  • Renewable Energy, Sustainability and the Environment
  • Hardware and Architecture
  • Control and Optimization
  • Computational Theory and Mathematics


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