A Cyber Threat Intelligence Sharing Scheme Based on Consortium Blockchain in the Energy Industry

Cyber threat intelligence sharing enhances situational awareness among stakeholders and is crucial for safeguarding key energy assets. In view of the problems of intelligence tampering, uneven intelligence quality and lack of incentives in the current threat intelligence sharing scheme, we proposed a cyber threat intelligence sharing scheme for the energy industry based on the consortium chain. In this scheme, the energy industry deployed distributed honeynet to actively trap valuable threat intelligence information and then shared it. Firstly, the server stored encrypted threat intelligence, the private chain stored ciphertext hash values, and the consortium chain stored encrypted keywords to ensure the security and privacy of threat intelligence. Secondly, we set up the validator sharing subject to evaluate the level of cyber threat intelligence and set an incentive strategy. Then, we implemented secure search for keywords based on searchable encryption and secure intelligence sharing based on proxy re-encryption. Finally, we perform a security and privacy protection analysis of the proposed scheme, and the results demonstrate that it outperforms existing intelligence sharing schemes in both performance and privacy protection effectiveness.

Authors

Institutions

Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/isaeece66033.2025.11160256
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Cyber Threat Intelligence Sharing Scheme Based on Consortium Blockchain in the Energy Industry

Tianfu Xu, Zhiyuan Luo, X. Bai, Kai Chen et al.
Information and Cyber Security
article

A Cyber Threat Intelligence Sharing Scheme Based on Consortium Blockchain in the Energy Industry

Tianfu Xu, Zhiyuan Luo, X. Bai, Kai Chen, Yunqing Hu, Rixuan Qiu, Qun He, Xinyu Gao
article en

Abstract

Cyber threat intelligence sharing enhances situational awareness among stakeholders and is crucial for safeguarding key energy assets. In view of the problems of intelligence tampering, uneven intelligence quality and lack of incentives in the current threat intelligence sharing scheme, we proposed a cyber threat intelligence sharing scheme for the energy industry based on the consortium chain. In this scheme, the energy industry deployed distributed honeynet to actively trap valuable threat intelligence information and then shared it. Firstly, the server stored encrypted threat intelligence, the private chain stored ciphertext hash values, and the consortium chain stored encrypted keywords to ensure the security and privacy of threat intelligence. Secondly, we set up the validator sharing subject to evaluate the level of cyber threat intelligence and set an incentive strategy. Then, we implemented secure search for keywords based on searchable encryption and secure intelligence sharing based on proxy re-encryption. Finally, we perform a security and privacy protection analysis of the proposed scheme, and the results demonstrate that it outperforms existing intelligence sharing schemes in both performance and privacy protection effectiveness.

North China Electric Power University (CN), State Grid Corporation of China (China) (CN), Shanghai Electric (China) (CN), China Power Engineering Consulting Group (China) (CN)
Openalex Percentile: Top 62%
Information and Cyber Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Cyber Threat Intelligence Sharing Scheme Based on Consortium Blockchain in the Energy Industry — Tianfu Xu, Zhiyuan Luo, et al. · (2025) | TGRS Research Map | TGRS