Cybersecurity-Aware Decentralized Machine Learning Framework for Construction Equipment Motion Recognition Using Blockchain

11 pages•Published: August 28, 2025

Chengliang Zheng, Xingyu Tao, Jiarui Lin, Moumita Das, Wenchi Shou and Jack C.P. Cheng

Abstract

Artificial intelligence (AI) is playing an increasing role in the construction industry to enhance productivity, reduce safety accidents, and optimize collaboration efficiency. However, attacks on AI systems also introduce cybersecurity threats that could lead to severe consequences, such as equipment damage, financial loss, operational downtime, safety accidents, and potential loss of life. Motivated by the construction industry's limited efforts to defend against AI cybersecurity vulnerabilities—a result of a lack of awareness and IT resources—this paper aims to propose a cybersecurity-aware decentralized machine learning (CADML) framework to protect the life cycle cybersecurity of machine learning (ML) models leveraging blockchain. First, the workflow of the CADML framework will be introduced to illustrate the logic of blockchain-ML integration. Second, a new blockchain smart contract algorithm, ML-embed smart contract (MLSC), will be developed to train and apply AI in a decentralized manner. The primary innovation framework extends current "partially" blockchain-ML integration methods to enable the ML's "lifecycle" (from raw data storage, training, implementation, to model update) to operate in a decentralized and secure blockchain environment. The framework is tested to recognize construction equipment motions. Results show that (1) the ML model could be successfully trained and implemented within a blockchain and (2) the ML performance (accuracy, precision, and recall) is acceptable.

Keyphrases: blockchain, construction equipment, machine learning, motion recognition, smart contract

In: Jack Cheng and Yu Yantao (editors). Proceedings of The Sixth International Conference on Civil and Building Engineering Informatics, vol 22, pages 1102-1112.

Links:	https://easychair.org/publications/paper/tmZR
	https://doi.org/10.29007/lvjg

BibTeX entry

@inproceedings{ICCBEI2025:Cybersecurity_Aware_Decentralized_Machine,
  author    = {Chengliang Zheng and Xingyu Tao and Jiarui Lin and Moumita Das and Wenchi Shou and Jack C.P. Cheng},
  title     = {Cybersecurity-Aware Decentralized Machine Learning Framework for Construction Equipment Motion Recognition Using Blockchain},
  booktitle = {Proceedings of The Sixth International Conference on Civil and Building Engineering Informatics},
  editor    = {Jack Cheng and Yu Yantao},
  series    = {Kalpa Publications in Computing},
  volume    = {22},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/tmZR},
  doi       = {10.29007/lvjg},
  pages     = {1102-1112},
  year      = {2025}}

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