Shigeng Zhang

About Shigeng Zhang

Shigeng Zhang, With an exceptional h-index of 29 and a recent h-index of 23 (since 2020), a distinguished researcher at Central South University, specializes in the field of Internet of Things, Security of IoT, AI Security, Edge Intelligence, RFID systems.

His recent articles reflect a diverse array of research interests and contributions to the field:

Foolmix: Strengthen the Transferability of Adversarial Examples by Dual-Blending and Direction Update Strategy

Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning

Universal and Scalable Weakly-supervised Domain Adaptation

UCG: A Universal Cross-Domain Generator for Transferable Adversarial Examples

An Edge-oriented Deep Learning Model Security Assessment Framework

CMMR: A Composite Multidimensional Models Robustness Evaluation Framework for Deep Learning

LSD: Adversarial Examples Detection Based on Label Sequences Discrepancy

TransAST: A Machine Translation-Based Approach for Obfuscated Malicious JavaScript Detection

Shigeng Zhang Information

University

Position

___

Citations(all)

3097

Citations(since 2020)

1770

Cited By

2017

hIndex(all)

29

hIndex(since 2020)

23

i10Index(all)

64

i10Index(since 2020)

45

Email

University Profile Page

Google Scholar

Shigeng Zhang Skills & Research Interests

Internet of Things

Security of IoT

AI Security

Edge Intelligence

RFID systems

Top articles of Shigeng Zhang

Foolmix: Strengthen the Transferability of Adversarial Examples by Dual-Blending and Direction Update Strategy

IEEE Transactions on Information Forensics and Security

2024/4/25

Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Universal and Scalable Weakly-supervised Domain Adaptation

IEEE Transactions on Image Processing

2024/2/8

UCG: A Universal Cross-Domain Generator for Transferable Adversarial Examples

IEEE Transactions on Information Forensics and Security

2024/1/11

An Edge-oriented Deep Learning Model Security Assessment Framework

2023/12/21

CMMR: A Composite Multidimensional Models Robustness Evaluation Framework for Deep Learning

2023/10/20

LSD: Adversarial Examples Detection Based on Label Sequences Discrepancy

IEEE Transactions on Information Forensics and Security

2023/8/11

TransAST: A Machine Translation-Based Approach for Obfuscated Malicious JavaScript Detection

2023/6/27

PEiD: Precise and Real-Time LOS/NLOS Path Identification Based on Peak Energy Index Distribution

Applied Sciences

2023/6/23

Accurate IoT Device Identification based on A Few Network Traffic

2023/6/19

A Fast Adversarial Sample Detection Approach for Industrial Internet-of-Things Applications

2023/6/19

A Few-shot-learning-based Method to Object Recognition in Multiple Scenarios

2023/6/19

Xuan Liu
Xuan Liu

H-Index: 2

Shigeng Zhang
Shigeng Zhang

H-Index: 19

Backdoor Attacks to Deep Learning Models and Countermeasures: A Survey

IEEE Open Journal of the Computer Society

2023/4/14

ImageDroid: Using deep learning to efficiently detect Android malware and automatically mark malicious features

Security and Communication Networks

2023/4/7

An Efficient RFID Tag Search Protocol Based on Historical Information Reasoning for Intelligent Farm Management

ACM Transactions on Sensor Networks

2023

Xuan Liu
Xuan Liu

H-Index: 2

Shigeng Zhang
Shigeng Zhang

H-Index: 19

Multi-task adversarial learning for semi-supervised trajectory-user linking

2022/9/19

Encoding-based Range Detection in Commodity RFID Systems

2022/5/2

An optimal deployment scheme for extremely fast charging stations

Peer-to-Peer Networking and Applications

2022/5

Fgl_droid: An efficient android malware detection method based on hybrid analysis

Security and Communication Networks

2022/4/28

More than scheduling: novel and efficient coordination algorithms for multiple readers in RFID systems

IEEE Transactions on Mobile Computing

2022/4/19

See List of Professors in Shigeng Zhang University(Central South University)

Co-Authors

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