Zhiqiang Wang
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
Zhiqiang Wang has a total of 172 co-authors. Here are the top co-authors by number of shared publications:
Tao Yang
Key Lab of Information Network Security, Ministry of Public Security
8 shared publicationsShaowei Yuan
Beijing Electronic Science and Technology Institute
7 shared publicationsYaping Chi
Beijing Electronic Science and Technology Institute
7 shared publications- Jianyi Zhang
Beijing Electronic Science and Technology Institute
6 shared publications Ruoxi Cheng
Beijing Electronic Science and Technology Institute
6 shared publicationsYizhong Ding
Beijing Electronic Science and Technology Institute
6 shared publications
Latest Publications
- 8 October 2026
- Published by Springer Nature
- p. 244-263
AutoVulnPHP: LLM-Powered Two-Stage PHP Vulnerability Detection and Automated Localization
- 8 October 2026
- Published by Springer Nature
- p. 244-263
AutoVulnPHP: LLM-Powered Two-Stage PHP Vulnerability Detection and Automated Localization
- 8 September 2026
- Published by Springer Nature
- p. 265-281
DHGNN-MambaNet: Encrypted Traffic Analysis Based on Dual-Granularity Heterogeneous Graphs and Bidirectional Mamba
- 8 September 2026
- Published by Springer Nature
- p. 265-281
DHGNN-MambaNet: Encrypted Traffic Analysis Based on Dual-Granularity Heterogeneous Graphs and Bidirectional Mamba
- 21 August 2026
- Published by Elsevier in Expert Systems with Applications
- Vol. 333
Multiresolution cryptocurrency forecasting with audit-oriented KAN mappings
- 21 August 2026
- Published by Elsevier in Expert Systems with Applications
- Vol. 333
Multiresolution cryptocurrency forecasting with audit-oriented KAN mappings
- Open Access
- 13 August 2026
- Published by Springer Nature in Journal of King Saud University Computer and Information Sciences
- Vol. 38 (6) , 616
Toward privacy-accountable authentication in vehicular networks: An HQC-based context-aware linkable ring signature scheme
- 13 August 2026
- Published by Springer Nature in Journal of King Saud University Computer and Information Sciences
- Vol. 38 (6) , 616
Open AccessToward privacy-accountable authentication in vehicular networks: An HQC-based context-aware linkable ring signature scheme
- 18 July 2026
- Published by Springer Nature
- p. 292-311
Detection and Interpretation of Malicious Network Traffic via a Novel 8-Channel Image Representation
- 18 July 2026
- Published by Springer Nature
- p. 292-311
Detection and Interpretation of Malicious Network Traffic via a Novel 8-Channel Image Representation
- 17 July 2026
- Published by Springer Nature
- p. 308-324
MALDroid: An Explainable Android Malware Detection Framework Leveraging Temporal and Semantic Contextual Features
- 17 July 2026
- Published by Springer Nature
- p. 308-324
MALDroid: An Explainable Android Malware Detection Framework Leveraging Temporal and Semantic Contextual Features
- 17 July 2026
- Published by Springer Nature
- p. 570-585
A Malicious IoT Traffic Detection Method Based on Recursive Feature Addition Using Graph Neural Network
- 17 July 2026
- Published by Springer Nature
- p. 570-585
A Malicious IoT Traffic Detection Method Based on Recursive Feature Addition Using Graph Neural Network
- 17 July 2026
- Published by Springer Nature
- p. 543-558
FedHAP-MTD: Personalized Federated Malicious Traffic Detection Based on Hierarchical Updating and Adaptive Learning
- 17 July 2026
- Published by Springer Nature
- p. 543-558
FedHAP-MTD: Personalized Federated Malicious Traffic Detection Based on Hierarchical Updating and Adaptive Learning
- 3 June 2026
- Published by Springer Nature
- p. 20-35
MFETD: Multimodal Feature Fusion for Encrypted Traffic Detection Based on Transformer
- 3 June 2026
- Published by Springer Nature
- p. 20-35
MFETD: Multimodal Feature Fusion for Encrypted Traffic Detection Based on Transformer
- 11 February 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Internet of Things Journal
- Vol. 13 (9) , 19600-19615
A Passive Network Storage Covert Channel for Internet of Things
Network covert channels in the Internet of Things (IoT) can conceal device communication behaviors, thereby protecting user privacy and ensuring secure transmission of sensitive data. However, existing active covert channels in the IoT are constrained by the low computational power and limited storage of IoT terminal devices, making them unsuitable for complex steganographic algorithms. Moreover, the active covert channel is more vulnerable to targeted detection and blocking by traffic analysis. To address these challenges, this study proposes a passive network storage covert channel (PNSCC) that leverages intermediate IoT nodes. We also present solutions for synchronization and reversible data hiding within the PNSCC. A covert channel kernel module was designed and deployed on smart routers running the OpenWrt system, followed by the experimental testing. The results indicate that the PNSCC achieves a relatively high capacity, with a covert data transmission rate of approximately 88.97 b/s in real-world network environments. Additionally, it has minimal impact on actual network performance and exhibits resilience against traffic analysis.
- 11 February 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Internet of Things Journal
- Vol. 13 (9) , 19600-19615
A Passive Network Storage Covert Channel for Internet of Things
Network covert channels in the Internet of Things (IoT) can conceal device communication behaviors, thereby protecting user privacy and ensuring secure transmission of sensitive data. However, existing active covert channels in the IoT are constrained by the low computational power and limited storage of IoT terminal devices, making them unsuitable for complex steganographic algorithms. Moreover, the active covert channel is more vulnerable to targeted detection and blocking by traffic analysis. To address these challenges, this study proposes a passive network storage covert channel (PNSCC) that leverages intermediate IoT nodes. We also present solutions for synchronization and reversible data hiding within the PNSCC. A covert channel kernel module was designed and deployed on smart routers running the OpenWrt system, followed by the experimental testing. The results indicate that the PNSCC achieves a relatively high capacity, with a covert data transmission rate of approximately 88.97 b/s in real-world network environments. Additionally, it has minimal impact on actual network performance and exhibits resilience against traffic analysis.