Shuo Wang

Orcid: 0000-0001-8938-2364

Affiliations:
  • Monash University, Melbourne, CSIRO, Data61, Cybersecurity CRC, Australia
  • University of Melbourne, Computing and Information Systems, Australia (PhD 2018)


According to our database1, Shuo Wang authored at least 63 papers between 2016 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
A Multi-Task Adversarial Attack against Face Authentication.
ACM Trans. Multim. Comput. Commun. Appl., November, 2024

On Model Outsourcing Adaptive Attacks to Deep Learning Backdoor Defenses.
IEEE Trans. Inf. Forensics Secur., 2024

SoK: Can Trajectory Generation Combine Privacy and Utility?
Proc. Priv. Enhancing Technol., 2024

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

A Multi-task Adversarial Attack Against Face Authentication.
CoRR, 2024

DeepiSign-G: Generic Watermark to Stamp Hidden DNN Parameters for Self-contained Tracking.
CoRR, 2024

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

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

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

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

How to Efficiently Manage Critical Infrastructure Vulnerabilities? Toward Large Code-graph Models.
Proceedings of the 1st ACM Workshop on Large AI Systems and Models with Privacy and Safety Analysis, 2024

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

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

Text classification on heterogeneous information network via enhanced GCN and knowledge.
Neural Comput. Appl., July, 2023

Defeating Misclassification Attacks Against Transfer Learning.
IEEE Trans. Dependable Secur. Comput., 2023

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

PublicCheck: Public Integrity Verification for Services of Run-time Deep Models.
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

DOITRUST: Dissecting On-chain Compromised Internet Domains via Graph Learning.
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

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

DeepTaster: Adversarial Perturbation-Based Fingerprinting to Identify Proprietary Dataset Use in Deep Neural Networks.
Proceedings of the Annual Computer Security Applications Conference, 2023

2022
Defending Adversarial Attacks via Semantic Feature Manipulation.
IEEE Trans. Serv. Comput., 2022

Backdoor Attacks Against Transfer Learning With Pre-Trained Deep Learning Models.
IEEE Trans. Serv. Comput., 2022

OCTOPUS: Overcoming Performance and Privatization Bottlenecks in Distributed Learning.
IEEE Trans. Parallel Distributed Syst., 2022

Adversarial Detection by Latent Style Transformations.
IEEE Trans. Inf. Forensics Secur., 2022

Tracking Dataset IP Use in Deep Neural Networks.
CoRR, 2022

Towards Web Phishing Detection Limitations and Mitigation.
CoRR, 2022

Integrity Fingerprinting of DNN with Double Black-box Design and Verification.
CoRR, 2022

R-Net: Robustness Enhanced Financial Time-Series Prediction with Differential Privacy.
Proceedings of the International Joint Conference on Neural Networks, 2022

Latent Space-Based Backdoor Attacks Against Deep Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2022

Reconstruction Attack on Differential Private Trajectory Protection Mechanisms.
Proceedings of the Annual Computer Security Applications Conference, 2022

2021
"Who Wants to Know all this Stuff?!": Understanding Older Adults' Privacy Concerns in Aged Care Monitoring Devices.
Interact. Comput., 2021

Robust Training Using Natural Transformation.
CoRR, 2021

OCTOPUS: Overcoming Performance andPrivatization Bottlenecks in Distributed Learning.
CoRR, 2021

Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition.
Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021

Projective Ranking: A Transferable Evasion Attack Method on Graph Neural Networks.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Adversarial Defense by Latent Style Transformations.
CoRR, 2020

Defending Adversarial Attacks via Semantic Feature Manipulation.
CoRR, 2020

Generating Semantic Adversarial Examples via Feature Manipulation.
CoRR, 2020

Multivariate Financial Time-Series Prediction With Certified Robustness.
IEEE Access, 2020

Privacy-Preserving Data Generation and Sharing Using Identification Sanitizer.
Proceedings of the Web Information Systems Engineering - WISE 2020, 2020

Privacy by Design in Aged Care Monitoring Devices? Well, Not Quite Yet!
Proceedings of the OzCHI '20: 32nd Australian Conference on Human-Computer-Interaction, 2020

OIAD: One-for-all Image Anomaly Detection with Disentanglement Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

PART-GAN: Privacy-Preserving Time-Series Sharing.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

2019
Defending Against Misclassification Attacks in Transfer Learning.
CoRR, 2019

P-STM: Privacy-Protected Social Tie Mining of Individual Trajectories.
Proceedings of the 2019 IEEE International Conference on Web Services, 2019

Parametric Canonical Correlation Analysis.
Proceedings of the 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), 2019

2018
Privacy-protected statistics publication over social media user trajectory streams.
Future Gener. Comput. Syst., 2018

P-GENT: Privacy-Preserving Geocoding of Non-Geotagged Tweets.
Proceedings of the 17th IEEE International Conference On Trust, 2018

PAIRS: Privacy-Aware Identification and Recommendation of Spatio-Friends.
Proceedings of the 17th IEEE International Conference On Trust, 2018

A Privacy-Preserving Semantic Annotation Framework Using Online Social Media.
Proceedings of the Web Services - ICWS 2018, 2018

2017
Protecting personal trajectories of social media users through differential privacy.
Comput. Secur., 2017

Sensitive gazetteer discovery and protection for mobile social media users.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Privacy-protected place of activity mining on big location data.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Supporting geospatial privacy-preserving data mining of social media.
Soc. Netw. Anal. Min., 2016

Privacy-protected social media user trajectories calibration.
Proceedings of the 12th IEEE International Conference on e-Science, 2016

Protecting the location privacy of mobile social media users.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016


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