Hongpeng Bai
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Hongpeng Bai has a total of 20 co-authors. Here are the top co-authors by number of shared publications:
- Guangquan Xu
Tianjin University
3 shared publications - Haobo Zhang
Shihezi University, Shihezi
2 shared publications - Lingyue Li
Tianjin University
2 shared publications - Shunzhe Zhao
Shihezi University, Shihezi
2 shared publications - Yao Zhang
Tianjin University
2 shared publications - Yude Bai
Tiangong University
2 shared publications
Latest Publications
- 29 October 2026
- Published by Springer Nature
- p. 33-60
AndroTruth: A Reliable Benchmark Android Malware Dataset Derived from Technical Expert Reports
- 29 October 2026
- Published by Springer Nature
- p. 33-60
AndroTruth: A Reliable Benchmark Android Malware Dataset Derived from Technical Expert Reports
- 9 October 2026
- Published by Springer Nature
- p. 443-463
Two Byzantine-only Enhanced Incentive Attacks on Ethereum PoS
- 9 October 2026
- Published by Springer Nature
- p. 443-463
Two Byzantine-only Enhanced Incentive Attacks on Ethereum PoS
- Open Access
ThreatIntel-Andro: Expert-Verified Benchmarking for Robust Android Malware Research
The rapidly evolving Android malware ecosystem demands high-quality, real-time datasets as a foundation for effective detection and defense. With the widespread adoption of mobile devices across industrial systems, they have become a critical yet often overlooked attack surface in industrial cybersecurity. However, mainstream datasets widely used in academia and industry (e.g., Drebin) exhibit significant limitations: on one hand, their heavy reliance on VirusTotal's multi-engine aggregation results introduces substantial label noise; on the other hand, outdated samples reduce their temporal relevance. Moreover, automated labeling tools (e.g., AVClass2) suffer from suboptimal aggregation strategies, further compounding labeling errors and propagating inaccuracies throughout the research community.
Open AccessThreatIntel-Andro: Expert-Verified Benchmarking for Robust Android Malware Research
The rapidly evolving Android malware ecosystem demands high-quality, real-time datasets as a foundation for effective detection and defense. With the widespread adoption of mobile devices across industrial systems, they have become a critical yet often overlooked attack surface in industrial cybersecurity. However, mainstream datasets widely used in academia and industry (e.g., Drebin) exhibit significant limitations: on one hand, their heavy reliance on VirusTotal's multi-engine aggregation results introduces substantial label noise; on the other hand, outdated samples reduce their temporal relevance. Moreover, automated labeling tools (e.g., AVClass2) suffer from suboptimal aggregation strategies, further compounding labeling errors and propagating inaccuracies throughout the research community.
- Open Access
- 24 August 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (17) , 12841
Digital Technology and Green Development in Manufacturing: Evidence from China and 20 Other Asian Countries
The global interest in environmental protection and sustainable development has grown steadily in recent years, sparking widespread concern about green development in the manufacturing industry among governments, enterprises, and scholars around the world. Despite this heightened interest, research on the influence of the digital economy on the manufacturing industry’s green development remains scarce. This article analyzes the impact of the digital economy on the green development of the manufacturing industry and examines the role of human capital and trade competitiveness in this context. Using a two-way fixed-effects model of panel data analysis, we investigated the GTFP (Green Total Factor Productivity) of the Chinese manufacturing industry, as well as that of the overall industry and 20 other Asian countries along the “Belt and Road”. Our findings indicate a positive association between the digital economy and both the overall GTFP and the manufacturing GTFP in China. The countries situated along the Belt and Road experience a U-shaped trend in their GTFP due to the impact of the digital economy. The digital economy displays a delayed impact, and its eco-friendly value is realized, to different extents, after two sequential periods. In addition, human capital and trade competitiveness are threshold variables in the relationship between the digital economy and the green development of the manufacturing industry. When human capital exceeds a certain threshold and trade competitiveness exceeds a certain threshold, the digital economy has a positive effect on GTFP. This study offers unique insights into the impact of the digital economy on the green development of the manufacturing industry. By addressing this research gap, this study gives policymakers the ability to leverage these findings to promote sustainable practices across the industry. Ultimately, the valuable insights provided by this study may contribute to the ongoing efforts to advance the green development of the manufacturing industry.
- 24 August 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (17) , 12841
Open AccessDigital Technology and Green Development in Manufacturing: Evidence from China and 20 Other Asian Countries
The global interest in environmental protection and sustainable development has grown steadily in recent years, sparking widespread concern about green development in the manufacturing industry among governments, enterprises, and scholars around the world. Despite this heightened interest, research on the influence of the digital economy on the manufacturing industry’s green development remains scarce. This article analyzes the impact of the digital economy on the green development of the manufacturing industry and examines the role of human capital and trade competitiveness in this context. Using a two-way fixed-effects model of panel data analysis, we investigated the GTFP (Green Total Factor Productivity) of the Chinese manufacturing industry, as well as that of the overall industry and 20 other Asian countries along the “Belt and Road”. Our findings indicate a positive association between the digital economy and both the overall GTFP and the manufacturing GTFP in China. The countries situated along the Belt and Road experience a U-shaped trend in their GTFP due to the impact of the digital economy. The digital economy displays a delayed impact, and its eco-friendly value is realized, to different extents, after two sequential periods. In addition, human capital and trade competitiveness are threshold variables in the relationship between the digital economy and the green development of the manufacturing industry. When human capital exceeds a certain threshold and trade competitiveness exceeds a certain threshold, the digital economy has a positive effect on GTFP. This study offers unique insights into the impact of the digital economy on the green development of the manufacturing industry. By addressing this research gap, this study gives policymakers the ability to leverage these findings to promote sustainable practices across the industry. Ultimately, the valuable insights provided by this study may contribute to the ongoing efforts to advance the green development of the manufacturing industry.