Cheng Zhang

Orcid: 0000-0001-8721-0577

Affiliations:
  • China University of Mining and Technology, School of Computer Science and Technology, Xuzhou, China


According to our database1, Cheng Zhang authored at least 13 papers between 2022 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
MSSN: Multi-Stream Steganalysis Network for Detection of QIM-Based Steganography in VoIP Streams.
IEEE Trans. Dependable Secur. Comput., 2026

Cross-Domain detection of AI-Generated text: Integrating linguistic richness and lexical pair dispersion via deep learning.
Pattern Recognit. Lett., 2026

2025
Efficient Detection of QIM-Based VoIP Steganography Using Adjacent Frame Integration and Multi-Codeword Priority Attention.
IEEE Signal Process. Lett., 2025

CAST: Contrastive Analysis of Spatial and Temporal Features for QIM-Based VoIP Steganalysis.
IEEE Signal Process. Lett., 2025

2024
Improving fault localization via weighted execution graph and graph attention network.
J. Softw. Evol. Process., June, 2024

Detection of QIM-Based Steganography in VoIP Streams: A MobileViT-Inspired Model.
IEEE Signal Process. Lett., 2024

TENet: leveraging transformer encoders for steganalysis of QIM steganography in VoIP speech streams.
Multim. Tools Appl., 2024

Practical Deep Learning Models for QIM-based VoIP Steganalysis.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

2023
An effective fault localization approach based on PageRank and mutation analysis.
J. Syst. Softw., October, 2023

A fault localization approach based on fault propagation context.
Inf. Softw. Technol., August, 2023

Frame-level steganalysis of QIM steganography in compressed speech based on multi-dimensional perspective of codeword correlations.
J. Ambient Intell. Humaniz. Comput., July, 2023

Speech Emotion Recognition Method Based on Cross-Layer Intersectant Fusion.
IAIC (2), 2023

2022
A Fault Localization Approach Based on BiRNN and Multi-Dimensional Features.
Int. J. Softw. Eng. Knowl. Eng., 2022


  Loading...