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Minhui Xue — most-cited papers & profile · Cybersecurity
← authors
·
overview
Minhui Xue
32
papers ·
387
citations ·
27
h-index
Commonwealth Scientific and Industrial Research Organisation · The University of Adelaide
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Most-cited papers
Automated Poisoning Attacks and Defenses in Malware Detection Systems: An Adversarial Machine Learning Approach
2017 · 243 citations
Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization
2019 · 44 citations
Differentially Private Data Generative Models
2018 · 32 citations
Deep Learning Backdoors
2020 · 7 citations
Quantization Backdoors to Deep Learning Commercial Frameworks
2021 · 7 citations
Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense
2023 · 4 citations
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations
2022 · 3 citations
The Philosopher's Stone: Trojaning Plugins of Large Language Models
2023 · 3 citations
The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices
2022 · 2 citations
DeepTheft: Stealing DNN Model Architectures through Power Side Channel
2023 · 2 citations
Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification
2023 · 2 citations
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning
2024 · 2 citations
With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models
2020 · 1 citations
A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services
2023 · 1 citations
DPAgent-in-the-Middle: Agentic Defense and Repair Against AI-Groomed Deceptive Patterns
2026
Top co-authors
Haojin Zhu
· 6
Ruoxi Sun
· 5
Benjamin Zi Hao Zhao
· 4
Shaofeng Li
· 4
Shuo Wang
· 4
Alsharif Abuadbba
· 3
Anmin Fu
· 3
Bo Li
· 3
Derui Wang
· 3
Hua Ma
· 3
Huming Qiu
· 3
Surya Nepal
· 3
Topics
Adversarial ML
Vulnerability Detection
Threat Intelligence
Privacy
Malware Detection
LLM Security
Network Security
Anomaly Detection
Forensics