Yu Cheng
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Yu Cheng has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Xiaofang Qi
School of Computer Science and Engineering, Southeast University, Nanjing, China
3 shared publications Ri-Gui Zhou
College of Information Engineering, Shanghai Maritime University, Shanghai, China
2 shared publicationsDaQian Liu
College of Information Engineering, Shanghai Maritime University, Shanghai, China
1 shared publicationHan Yu
College of Information Engineering, Shanghai Maritime University, Shanghai, China
1 shared publicationNan Jiang
College of Computer, Beijing University of Technology, Beijing, China
1 shared publicationYanhui Li
1 shared publication
Latest Publications
- Open Access
- 14 January 2026
- Published by Springer Nature in Cybersecurity
- Vol. 9 (1) , 104
Investigating red packet fraud in android applications: insights from user reviews
With the popularization of smartphones, red packets have been widely used in mobile apps. However, the issues of fraud associated with them have also become increasingly prominent. As reported in user reviews from mobile app markets, many users have complained about experiencing red packet fraud and being persistently troubled by fraudulent red packets. To uncover this phenomenon, we conduct the first investigation into an extensive collection of user reviews on apps with red packets. In this paper, we first propose a novel automated approach, ReckDetector, for effectively identifying apps with red packets from app markets. We then collect over 360,000 real user reviews from 334 apps with red packets available on Google Play and three popular alternative Android app markets. We preprocess the user reviews to extract those related to red packets and fine-tune a pre-trained BERT model to identify negative reviews. Finally, based on semantic analysis, we have summarized six distinct categories of red packet fraud issues reported by users. Through our study, we found that red packet fraud is highly prevalent, significantly impacting user experience and damaging the reputation of apps. Moreover, red packets have been widely exploited by unscrupulous app developers as a deceptive incentive mechanism to entice users into completing their designated tasks, thereby maximizing their profits.
- 14 January 2026
- Published by Springer Nature in Cybersecurity
- Vol. 9 (1) , 104
Open AccessInvestigating red packet fraud in android applications: insights from user reviews
With the popularization of smartphones, red packets have been widely used in mobile apps. However, the issues of fraud associated with them have also become increasingly prominent. As reported in user reviews from mobile app markets, many users have complained about experiencing red packet fraud and being persistently troubled by fraudulent red packets. To uncover this phenomenon, we conduct the first investigation into an extensive collection of user reviews on apps with red packets. In this paper, we first propose a novel automated approach, ReckDetector, for effectively identifying apps with red packets from app markets. We then collect over 360,000 real user reviews from 334 apps with red packets available on Google Play and three popular alternative Android app markets. We preprocess the user reviews to extract those related to red packets and fine-tune a pre-trained BERT model to identify negative reviews. Finally, based on semantic analysis, we have summarized six distinct categories of red packet fraud issues reported by users. Through our study, we found that red packet fraud is highly prevalent, significantly impacting user experience and damaging the reputation of apps. Moreover, red packets have been widely exploited by unscrupulous app developers as a deceptive incentive mechanism to entice users into completing their designated tasks, thereby maximizing their profits.
- 12 September 2024
- Published by Elsevier in Computers & Security
- Vol. 148
ReckDroid: Detecting red packet fraud in Android apps
- 12 September 2024
- Published by Elsevier in Computers & Security
- Vol. 148
ReckDroid: Detecting red packet fraud in Android apps
- 12 September 2020
- Published by Springer Nature in Quantum Information Processing
- Vol. 19 (9) , 1-20
Asymmetric scaling scheme over the two dimensions of a quantum image
- 12 September 2020
- Published by Springer Nature in Quantum Information Processing
- Vol. 19 (9) , 1-20
Asymmetric scaling scheme over the two dimensions of a quantum image
- 17 July 2019
- Published by Springer Nature in Quantum Information Processing
- Vol. 18 (9) , 1-19
Quantum image scaling based on bilinear interpolation with arbitrary scaling ratio
- 17 July 2019
- Published by Springer Nature in Quantum Information Processing
- Vol. 18 (9) , 1-19
Quantum image scaling based on bilinear interpolation with arbitrary scaling ratio