Minhui Xue

Orcid: 0000-0002-9172-4252

Affiliations:
  • CSIRO Marsfield, NSW, Australia
  • University of Adelaide, SA, Australia
  • Macquarie University, Australia (former)


According to our database1, Minhui Xue authored at least 143 papers between 2015 and 2024.

Collaborative distances:

Timeline

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Bibliography

2024
NTD: Non-Transferability Enabled Deep Learning Backdoor Detection.
IEEE Trans. Inf. Forensics Secur., 2024

The "Code" of Ethics: A Holistic Audit of AI Code Generators.
IEEE Trans. Dependable Secur. Comput., 2024

Quantization Backdoors to Deep Learning Commercial Frameworks.
IEEE Trans. Dependable Secur. Comput., 2024

${\sf VeriDIP}$VeriDIP: Verifying Ownership of Deep Neural Networks Through Privacy Leakage Fingerprints.
IEEE Trans. Dependable Secur. Comput., 2024

Reconstruction of Differentially Private Text Sanitization via Large Language Models.
CoRR, 2024

Edge Unlearning is Not "on Edge"! An Adaptive Exact Unlearning System on Resource-Constrained Devices.
CoRR, 2024

Iterative Window Mean Filter: Thwarting Diffusion-based Adversarial Purification.
CoRR, 2024

Rethinking the Threat and Accessibility of Adversarial Attacks against Face Recognition Systems.
CoRR, 2024

QUEEN: Query Unlearning against Model Extraction.
CoRR, 2024

On Security Weaknesses and Vulnerabilities in Deep Learning Systems.
CoRR, 2024

Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure.
CoRR, 2024

Provably Unlearnable Examples.
CoRR, 2024

Privacy-Preserving and Fairness-Aware Federated Learning for Critical Infrastructure Protection and Resilience.
Proceedings of the ACM on Web Conference 2024, 2024

Cardinality Counting in "Alcatraz": A Privacy-aware Federated Learning Approach.
Proceedings of the ACM on Web Conference 2024, 2024

The Invisible Game on the Internet: A Case Study of Decoding Deceptive Patterns.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

GEES: Enabling Location Privacy-Preserving Energy Saving in Multi-Access Edge Computing.
Proceedings of the ACM on Web Conference 2024, 2024

PPVR: A Privacy-Preserving Approach for User Behaviors in VR.
Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, 2024

dp-promise: Differentially Private Diffusion Probabilistic Models for Image Synthesis.
Proceedings of the 33rd USENIX Security Symposium, 2024

DNN-GP: Diagnosing and Mitigating Model's Faults Using Latent Concepts.
Proceedings of the 33rd USENIX Security Symposium, 2024

Being Transparent is Merely the Beginning: Enforcing Purpose Limitation with Polynomial Approximation.
Proceedings of the 33rd USENIX Security Symposium, 2024

Yes, One-Bit-Flip Matters! Universal DNN Model Inference Depletion with Runtime Code Fault Injection.
Proceedings of the 33rd USENIX Security Symposium, 2024

Bounded and Unbiased Composite Differential Privacy.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

CORELOCKER: Neuron-level Usage Control.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

LACMUS: Latent Concept Masking for General Robustness Enhancement of DNNs.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

DeepTheft: Stealing DNN Model Architectures through Power Side Channel.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

LocalStyleFool: Regional Video Style Transfer Attack Using Segment Anything Model.
Proceedings of the IEEE Security and Privacy, 2024

Utilizing Large Language Models with Human Feedback Integration for Generating Dedicated Warning for Phishing Emails.
Proceedings of the 2nd ACM Workshop on Secure and Trustworthy Deep Learning Systems, 2024

ShapFuzz: Efficient Fuzzing via Shapley-Guided Byte Selection.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

Iterative Search Attribution for Deep Neural Networks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

AttEXplore: Attribution for Explanation with model parameters eXploration.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning with Mixture of Prototypes for Out-of-Distribution Detection.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense.
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

LAMPS '24: ACM CCS Workshop on Large AI Systems and Models with Privacy and Safety Analysis.
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

MFABA: A More Faithful and Accelerated Boundary-Based Attribution Method for Deep Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Efficient Constrained K-center Clustering with Background Knowledge.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

LogoStyleFool: Vitiating Video Recognition Systems via Logo Style Transfer.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Data Hiding With Deep Learning: A Survey Unifying Digital Watermarking and Steganography.
IEEE Trans. Comput. Soc. Syst., December, 2023

An Explainability-Guided Testing Framework for Robustness of Malware Detectors.
Dataset, August, 2023

An Explainability-Guided Testing Framework for Robustness of Malware Detectors.
Dataset, August, 2023

Reinforcement Unlearning.
CoRR, 2023

Unleashing Cheapfakes through Trojan Plugins of Large Language Models.
CoRR, 2023

VeriDIP: Verifying Ownership of Deep Neural Networks through Privacy Leakage Fingerprints.
CoRR, 2023

Copyright Protection and Accountability of Generative AI: Attack, Watermarking and Attribution.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

AgrEvader: Poisoning Membership Inference against Byzantine-robust Federated Learning.
Proceedings of the ACM Web Conference 2023, 2023

Not Seen, Not Heard in the Digital World! Measuring Privacy Practices in Children's Apps.
Proceedings of the ACM Web Conference 2023, 2023

Detecting Union Type Confusion in Component Object Model.
Proceedings of the 32nd USENIX Security Symposium, 2023

RAI4IoE: Responsible AI for Enabling the Internet of Energy.
Proceedings of the 5th IEEE International Conference on Trust, 2023

PublicCheck: Public Integrity Verification for Services of Run-time Deep Models.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

StyleFool: Fooling Video Classification Systems via Style Transfer.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors.
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PPA: Preference Profiling Attack Against Federated Learning.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

DOITRUST: Dissecting On-chain Compromised Internet Domains via Graph Learning.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

The "Beatrix" Resurrections: Robust Backdoor Detection via Gram Matrices.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

RAI2: Responsible Identity Audit Governing the Artificial Intelligence.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

Demystifying Uneven Vulnerability of Link Stealing Attacks against Graph Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

FVW: Finding Valuable Weight on Deep Neural Network for Model Pruning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

POSTER: ML-Compass: A Comprehensive Assessment Framework for Machine Learning Models.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023

Unraveling Threat Intelligence Through the Lens of Malicious URL Campaigns.
Proceedings of the 18th Asian Internet Engineering Conference, 2023

Towards Better ML-Based Software Services: An Investigation of Source Code Engineering Impact.
Proceedings of the IEEE International Conference on Software Services Engineering, 2023

2022
Deep Learning Backdoors.
Security and Artificial Intelligence, 2022

Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples.
IEEE Trans. Neural Networks Learn. Syst., 2022

TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems.
IEEE Trans. Inf. Forensics Secur., 2022

Backdoors Against Natural Language Processing: A Review.
IEEE Secur. Priv., 2022

M^4I: Multi-modal Models Membership Inference.
CoRR, 2022

Cross-language Android permission specification.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

M$^4$I: Multi-modal Models Membership Inference.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Path Transitions Tell More: Optimizing Fuzzing Schedules via Runtime Program States.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Dissecting Malware in the Wild.
Proceedings of the ACSW 2022: Australasian Computer Science Week 2022, Brisbane, Australia, February 14, 2022

Statically Detecting Adversarial Malware through Randomised Chaining.
Proceedings of the ACSW 2022: Australasian Computer Science Week 2022, Brisbane, Australia, February 14, 2022

2021
With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models.
IEEE Trans. Inf. Forensics Secur., 2021

Invisible Backdoor Attacks on Deep Neural Networks Via Steganography and Regularization.
IEEE Trans. Dependable Secur. Comput., 2021

GUI-Squatting Attack: Automated Generation of Android Phishing Apps.
IEEE Trans. Dependable Secur. Comput., 2021

The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services.
Proc. Priv. Enhancing Technol., 2021

Exposing Weaknesses of Malware Detectors with Explainability-Guided Evasion Attacks.
CoRR, 2021

NatiDroid: Cross-Language Android Permission Specification.
CoRR, 2021

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography.
CoRR, 2021

Delayed Rewards Calibration via Reward Empirical Sufficiency.
CoRR, 2021

Explainability-based Backdoor Attacks Against Graph Neural Networks.
Proceedings of the WiseML@WiSec 2021: Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning, 2021

An Empirical Assessment of Global COVID-19 Contact Tracing Applications.
Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering, 2021

Dissecting Click Fraud Autonomy in the Wild.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Understanding and Detecting Mobile Ad Fraud Through the Lens of Invalid Traffic.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Hidden Backdoors in Human-Centric Language Models.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Snipuzz: Black-box Fuzzing of IoT Firmware via Message Snippet Inference.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Oriole: Thwarting Privacy Against Trustworthy Deep Learning Models.
Proceedings of the Information Security and Privacy - 26th Australasian Conference, 2021

2020
Deep Learning Backdoors.
CoRR, 2020

With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Online Regression Models.
CoRR, 2020

Vetting Security and Privacy of Global COVID-19 Contact Tracing Applications.
CoRR, 2020

iOS, Your OS, Everybody's OS: Vetting and Analyzing Network Services of iOS Applications.
Proceedings of the 29th USENIX Security Symposium, 2020

VenueTrace: a privacy-by-design COVID-19 digital contact tracing solution: poster abstract.
Proceedings of the SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems, 2020

Exploring the Eastern Frontier: A First Look at Mobile App Tracking in China.
Proceedings of the Passive and Active Measurement - 21st International Conference, 2020

An Automated Assessment of Android Clipboards.
Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, 2020

An empirical assessment of security risks of global Android banking apps.
Proceedings of the ICSE '20: 42nd International Conference on Software Engineering, Seoul, South Korea, 27 June, 2020

Quality Assessment of Online Automated Privacy Policy Generators: An Empirical Study.
Proceedings of the EASE '20: Evaluation and Assessment in Software Engineering, 2020

PALOR: Poisoning Attacks Against Logistic Regression.
Proceedings of the Information Security and Privacy - 25th Australasian Conference, 2020

2019
Invisible Backdoor Attacks Against Deep Neural Networks.
CoRR, 2019

The Audio Auditor: Participant-Level Membership Inference in Voice-Based IoT.
CoRR, 2019

Securing android applications via edge assistant third-party library detection.
Comput. Secur., 2019

DeepCT: Tomographic Combinatorial Testing for Deep Learning Systems.
Proceedings of the 26th IEEE International Conference on Software Analysis, 2019

Measuring and Analyzing Search Engine Poisoning of Linguistic Collisions.
Proceedings of the 2019 IEEE Symposium on Security and Privacy, 2019

No-jump-into-latency in China's internet!: toward last-mile hop count based IP geo-localization.
Proceedings of the International Symposium on Quality of Service, 2019

DeepHunter: a coverage-guided fuzz testing framework for deep neural networks.
Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2019

Sensing the Chinese Diaspora: How Mobile Apps Can Provide Insights Into Global Migration Flows.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018
Differentially Private Data Generative Models.
CoRR, 2018

Secure Deep Learning Engineering: A Software Quality Assurance Perspective.
CoRR, 2018

Coverage-Guided Fuzzing for Deep Neural Networks.
CoRR, 2018

Combinatorial Testing for Deep Learning Systems.
CoRR, 2018

AUSERA: Large-Scale Automated Security Risk Assessment of Global Mobile Banking Apps.
CoRR, 2018

Sensing the Chinese Diaspora: How Mobile Apps Can Provide Insights into Global Migration Flows.
CoRR, 2018

DeepGauge: Comprehensive and Multi-Granularity Testing Criteria for Gauging the Robustness of Deep Learning Systems.
CoRR, 2018

Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach.
Comput. Secur., 2018

Modeling Privacy Leakage Risks in Large-Scale Social Networks.
IEEE Access, 2018

FACTS: automated black-box testing of FinTech systems.
Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

Are mobile banking apps secure? what can be improved?
Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks.
Proceedings of the 25th Annual Network and Distributed System Security Symposium, 2018

DeepGauge: multi-granularity testing criteria for deep learning systems.
Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering, 2018

DeepMutation: Mutation Testing of Deep Learning Systems.
Proceedings of the 29th IEEE International Symposium on Software Reliability Engineering, 2018

APPCLASSIFIER: Automated App Inference on Encrypted Traffic via Meta Data Analysis.
Proceedings of the IEEE Global Communications Conference, 2018

2017
Characterizing user behaviors in location-based find-and-flirt services: Anonymity and demographics - A WeChat Case Study.
Peer-to-Peer Netw. Appl., 2017

Hardening Malware Detection Systems Against Cyber Maneuvers: An Adversarial Machine Learning Approach.
CoRR, 2017

Revisiting Localization Attacks in Mobile App People-Nearby Services.
Proceedings of the Security, Privacy, and Anonymity in Computation, Communication, and Storage, 2017

When program analysis meets mobile security: an industrial study of misusing Android internet sockets.
Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

Unleash the Power for Tensor: A Hybrid Malware Detection System Using Ensemble Classifiers.
Proceedings of the 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC), 2017

Fake reviews tell no tales? Dissecting click farming in content-generated social networks.
Proceedings of the 2017 IEEE/CIC International Conference on Communications in China, 2017

2016
Thwarting location privacy protection in location-based social discovery services.
Secur. Commun. Networks, 2016

The Right to be Forgotten in the Media: A Data-Driven Study.
Proc. Priv. Enhancing Technol., 2016

On the Impact of Location Errors on Localization Attacks in Location-Based Social Network Services.
Proceedings of the Security, Privacy, and Anonymity in Computation, Communication, and Storage, 2016

Towards adversarial detection of mobile malware: poster.
Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, 2016

You Can Yak but You Can't Hide: Localizing Anonymous Social Network Users.
Proceedings of the 2016 ACM on Internet Measurement Conference, 2016

POSTER: Accuracy vs. Time Cost: Detecting Android Malware through Pareto Ensemble Pruning.
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 2016

StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware.
Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, 2016

2015
Data-Driven Privacy Analytics: A WeChat Case Study in Location-Based Social Networks.
Proceedings of the Wireless Algorithms, Systems, and Applications, 2015

Attacks and Defenses in Location-Based Social Networks: A Heuristic Number Theory Approach.
Proceedings of the International Symposium on Security and Privacy in Social Networks and Big Data, 2015

I know where you are: Thwarting privacy protection in location-based social discovery services.
Proceedings of the 2015 IEEE Conference on Computer Communications Workshops, 2015

You Can Yak But You Can't Hide.
Proceedings of the 2015 ACM on Conference on Online Social Networks, 2015


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