Ho Bae

Orcid: 0000-0002-5238-3547

According to our database1, Ho Bae authored at least 21 papers between 2018 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Evaluation of Malware Classification Models for Heterogeneous Data.
Sensors, 2024

DAFA: Distance-Aware Fair Adversarial Training.
CoRR, 2024

2023
PixelSteganalysis: Pixel-Wise Hidden Information Removal With Low Visual Degradation.
IEEE Trans. Dependable Secur. Comput., 2023

Exploring Clustered Federated Learning's Vulnerability against Property Inference Attack.
Proceedings of the 26th International Symposium on Research in Attacks, 2023

PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

New Insights for the Stability-Plasticity Dilemma in Online Continual Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models.
Proceedings of the Computer Security - ESORICS 2023, 2023

Privacy-Preserving Publishing of Individual-Level Medical Data for Cloud Services.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
Data Embedding Scheme for Efficient Program Behavior Modeling With Neural Networks.
IEEE Trans. Emerg. Top. Comput. Intell., 2022

DNA Privacy: Analyzing Malicious DNA Sequences Using Deep Neural Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Membership Privacy-Preserving GAN.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
Learn2Evade: Learning-Based Generative Model for Evading PDF Malware Classifiers.
IEEE Trans. Artif. Intell., 2021

Gradient Masking of Label Smoothing in Adversarial Robustness.
IEEE Access, 2021

2020
Anomaly Detection by Learning Dynamics From a Graph.
IEEE Access, 2020

AnomiGAN: Generative Adversarial Networks for Anonymizing Private Medical Data.
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

2019
AnomiGAN: Generative adversarial networks for anonymizing private medical data.
CoRR, 2019

Comprehensive ensemble in QSAR prediction for drug discovery.
BMC Bioinform., 2019

Learning-Based Instantaneous Drowsiness Detection Using Wired and Wireless Electroencephalography.
IEEE Access, 2019

DNA Steganalysis Using Deep Recurrent Neural Networks.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

2018
Security and Privacy Issues in Deep Learning.
CoRR, 2018

Quantized Memory-Augmented Neural Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018


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