Shengshan Hu

Orcid: 0000-0003-0042-9045

According to our database1, Shengshan Hu authored at least 55 papers between 2015 and 2024.

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

Timeline

Legend:

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Bibliography

2024
Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples.
CoRR, 2024

Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Towards Model Extraction Attacks in GAN-Based Image Translation via Domain Shift Mitigation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
MISA: Unveiling the Vulnerabilities in Split Federated Learning.
CoRR, 2023

Robust Backdoor Detection for Deep Learning via Topological Evolution Dynamics.
CoRR, 2023

Corrupting Convolution-based Unlearnable Datasets with Pixel-based Image Transformations.
CoRR, 2023

Why Does Little Robustness Help? Understanding Adversarial Transferability From Surrogate Training.
CoRR, 2023

Feature Extraction Matters More: Universal Deepfake Disruption through Attacking Ensemble Feature Extractors.
CoRR, 2023

AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

A Four-Pronged Defense Against Byzantine Attacks in Federated Learning.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

PointCRT: Detecting Backdoor in 3D Point Cloud via Corruption Robustness.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Voice Guard: Protecting Voice Privacy with Strong and Imperceptible Adversarial Perturbation in the Time Domain.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Downstream-agnostic Adversarial Examples.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Masked Language Model Based Textual Adversarial Example Detection.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023

PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models against Adversarial Examples.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Optimizing Privacy-Preserving Outsourced Convolutional Neural Network Predictions.
IEEE Trans. Dependable Secur. Comput., 2022

Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation.
CoRR, 2022

Evaluating Membership Inference Through Adversarial Robustness.
Comput. J., 2022

Challenges and Approaches for Mitigating Byzantine Attacks in Federated Learning.
Proceedings of the IEEE International Conference on Trust, 2022

Shielding Federated Learning: Mitigating Byzantine Attacks with Less Constraints.
Proceedings of the 18th International Conference on Mobility, Sensing and Networking, 2022

BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Label.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Towards Privacy-Preserving Neural Architecture Search.
Proceedings of the IEEE Symposium on Computers and Communications, 2022

Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Attention Distraction: Watermark Removal Through Continual Learning with Selective Forgetting.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2022

Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
BOSSA: A Decentralized System for Proofs of Data Retrievability and Replication.
IEEE Trans. Parallel Distributed Syst., 2021

Shielding Collaborative Learning: Mitigating Poisoning Attacks Through Client-Side Detection.
IEEE Trans. Dependable Secur. Comput., 2021

Towards Private and Scalable Cross-Media Retrieval.
IEEE Trans. Dependable Secur. Comput., 2021

Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution.
IEEE Trans. Dependable Secur. Comput., 2021

Challenges and approaches for mitigating byzantine attacks in federated learning.
CoRR, 2021

Self-Supervised Adversarial Example Detection by Disentangled Representation.
CoRR, 2021

Shielding Federated Learning: A New Attack Approach and Its Defense.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2021

AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Feature-Indistinguishable Attack to Circumvent Trapdoor-Enabled Defense.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020
Optimizing Privacy-Preserving Outsourced Convolutional Neural Network Predictions.
CoRR, 2020

2019
Hidden Voice Commands: Attacks and Defenses on the VCS of Autonomous Driving Cars.
IEEE Wirel. Commun., 2019

Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection.
CoRR, 2019

Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution.
CoRR, 2019

VeriML: Enabling Integrity Assurances and Fair Payments for Machine Learning as a Service.
CoRR, 2019

Adversarial Examples for Automatic Speech Recognition: Attacks and Countermeasures.
IEEE Commun. Mag., 2019

2018
Outsourced Biometric Identification With Privacy.
IEEE Trans. Inf. Forensics Secur., 2018

InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy.
Proceedings of the 2018 IEEE Conference on Computer Communications, 2018

Searching an Encrypted Cloud Meets Blockchain: A Decentralized, Reliable and Fair Realization.
Proceedings of the 2018 IEEE Conference on Computer Communications, 2018

2017
Privacy-Preserving Outsourced Feature Extractions in the Cloud: A Survey.
IEEE Netw., 2017

Learning privately: Privacy-preserving canonical correlation analysis for cross-media retrieval.
Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

2016
Jamming-Resistant Multiradio Multichannel Opportunistic Spectrum Access in Cognitive Radio Networks.
IEEE Trans. Veh. Technol., 2016

Securing SIFT: Privacy-Preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.
IEEE Trans. Image Process., 2016

Securing Fast Learning! Ridge Regression over Encrypted Big Data.
Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA, 2016

Catch me in the dark: Effective privacy-preserving outsourcing of feature extractions over image data.
Proceedings of the 35th Annual IEEE International Conference on Computer Communications, 2016

Secure Surfing: Privacy-Preserving Speeded-Up Robust Feature Extractor.
Proceedings of the 36th IEEE International Conference on Distributed Computing Systems, 2016

SecHOG: Privacy-Preserving Outsourcing Computation of Histogram of Oriented Gradients in the Cloud.
Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, 2016

2015
CloudBI: Practical Privacy-Preserving Outsourcing of Biometric Identification in the Cloud.
Proceedings of the Computer Security - ESORICS 2015, 2015


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