Hongbin Liu

Orcid: 0000-0003-1869-0428

Affiliations:
  • Duke University, Durham, NC, USA


According to our database1, Hongbin Liu authored at least 21 papers between 2021 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Making LLMs Vulnerable to Prompt Injection via Poisoning Alignment.
CoRR, 2024

Automatically Generating Visual Hallucination Test Cases for Multimodal Large Language Models.
CoRR, 2024

Refusing Safe Prompts for Multi-modal Large Language Models.
CoRR, 2024

Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning.
CoRR, 2024

AudioMarkBench: Benchmarking Robustness of Audio Watermarking.
CoRR, 2024

Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models.
Proceedings of the 33rd USENIX Security Symposium, 2024

Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning.
Proceedings of the IEEE Security and Privacy, 2024

Data Poisoning Based Backdoor Attacks to Contrastive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Visual Hallucinations of Multi-modal Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Generation-based fuzzing? Don't build a new generator, reuse!
Comput. Secur., June, 2023

PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive Learning.
CoRR, 2022

StolenEncoder: Stealing Pre-trained Encoders.
CoRR, 2022

PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning.
Proceedings of the 31st USENIX Security Symposium, 2022

Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
10 Security and Privacy Problems in Self-Supervised Learning.
CoRR, 2021

On the Intrinsic Differential Privacy of Bagging.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

PointGuard: Provably Robust 3D Point Cloud Classification.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021


  Loading...