Wenbo Guo

Orcid: 0000-0002-6890-4503

Affiliations:
  • University of California Santa Barbara, CA, USA
  • Purdue University, West Lafayette, IN, USA (2023)
  • University of California Berkeley, CA, USA (2022 - 2023)
  • Pennsylvania State University, PA, USA (PhD 2022)


According to our database1, Wenbo Guo authored at least 38 papers between 2016 and 2023.

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Bibliography

2023
A NetAI Manifesto (Part II): Less Hubris, more Humility.
SIGMETRICS Perform. Evaluation Rev., September, 2023

TextGuard: Provable Defense against Backdoor Attacks on Text Classification.
CoRR, 2023

Deep Motion Masking for Secure, Usable, and Scalable Real-Time Anonymization of Virtual Reality Motion Data.
CoRR, 2023

netFound: Foundation Model for Network Security.
CoRR, 2023

Berkeley Open Extended Reality Recordings 2023 (BOXRR-23): 4.7 Million Motion Capture Recordings from 105, 852 Extended Reality Device Users.
CoRR, 2023

Inferring Private Personal Attributes of Virtual Reality Users from Head and Hand Motion Data.
CoRR, 2023

AIRS: Explanation for Deep Reinforcement Learning based Security Applications.
Proceedings of the 32nd USENIX Security Symposium, 2023

Unique Identification of 50, 000+ Virtual Reality Users from Head & Hand Motion Data.
Proceedings of the 32nd USENIX Security Symposium, 2023

PATROL: Provable Defense against Adversarial Policy in Two-player Games.
Proceedings of the 32nd USENIX Security Symposium, 2023

From Grim Reality to Practical Solution: Malware Classification in Real-World Noise.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

StateMask: Explaining Deep Reinforcement Learning through State Mask.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

BIRD: Generalizable Backdoor Detection and Removal for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

In Search of netUnicorn: A Data-Collection Platform to Develop Generalizable ML Models for Network Security Problems.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022
Are Shortest Rationales the Best Explanations for Human Understanding?
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

2021
CADE: Detecting and Explaining Concept Drift Samples for Security Applications.
Proceedings of the 30th USENIX Security Symposium, 2021

Adversarial Policy Training against Deep Reinforcement Learning.
Proceedings of the 30th USENIX Security Symposium, 2021

EDGE: Explaining Deep Reinforcement Learning Policies.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data.
Proceedings of the 28th Annual Network and Distributed System Security Symposium, 2021

BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

RNNRepair: Automatic RNN Repair via Model-based Analysis.
Proceedings of the 38th International Conference on Machine Learning, 2021

DANCE: Enhancing saliency maps using decoys.
Proceedings of the 38th International Conference on Machine Learning, 2021

Adversarial Policy Learning in Two-player Competitive Games.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Robust saliency maps with decoy-enhanced saliency score.
CoRR, 2020

Towards Inspecting and Eliminating Trojan Backdoors in Deep Neural Networks.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems.
CoRR, 2019

DEEPVSA: Facilitating Value-set Analysis with Deep Learning for Postmortem Program Analysis.
Proceedings of the 28th USENIX Security Symposium, 2019

Towards the Detection of Inconsistencies in Public Security Vulnerability Reports.
Proceedings of the 28th USENIX Security Symposium, 2019

Building Adversarial Defense with Non-invertible Data Transformations.
Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

RENN: Efficient Reverse Execution with Neural-Network-Assisted Alias Analysis.
Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering, 2019

2018
Active learning support vector machines with low-rank transformation.
Intell. Data Anal., 2018

Explaining Deep Learning Models - A Bayesian Non-parametric Approach.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Defending Against Adversarial Samples Without Security through Obscurity.
Proceedings of the IEEE International Conference on Data Mining, 2018

LEMNA: Explaining Deep Learning based Security Applications.
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017
Towards Interrogating Discriminative Machine Learning Models.
CoRR, 2017

Adversary Resistant Deep Neural Networks with an Application to Malware Detection.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016
Random Feature Nullification for Adversary Resistant Deep Architecture.
CoRR, 2016

Learning Adversary-Resistant Deep Neural Networks.
CoRR, 2016

Using Non-invertible Data Transformations to Build Adversary-Resistant Deep Neural Networks.
CoRR, 2016


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