- Information security
- Data Science
- ML/DL for Healthcare Applications
학력
박사과정, 정보통신대학원, 인하대학교
학술지 논문
(2024)
Hardening Interpretable Deep Learning Systems: Investigating Adversarial Threats and Defenses.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING.
21,
4
(2024)
MotionID: Towards practical behavioral biometrics-based implicit user authentication on smartphones.
PERVASIVE AND MOBILE COMPUTING.
101,
(2024)
Information fusion-based Bayesian optimized heterogeneous deep ensemble model based on longitudinal neuroimaging data.
APPLIED SOFT COMPUTING.
162,
1
(2024)
SingleADV: Single-Class Target-Specific Attack Against Interpretable Deep Learning Systems.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY.
19,
1
(2023)
Time-series visual explainability for Alzheimer's disease progression detection for smart healthcare.
ALEXANDRIA ENGINEERING JOURNAL.
82,
1
(2023)
Trustworthy artificial intelligence in Alzheimer’s disease: state of the art, opportunities, and challenges.
ARTIFICIAL INTELLIGENCE REVIEW.
56,
10
(2023)
Wildfire Susceptibility Mapping Using Deep Learning Algorithms in Two Satellite Imagery Dataset.
FORESTS.
14,
7
(2023)
Effective Multitask Deep Learning for IoT Malware Detection and Identification Using Behavioral Traffic Analysis.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT.
20,
2
(2023)
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence.
INFORMATION FUSION.
99,
1
(2023)
Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson?s disease.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE.
234,
1
(2023)
Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges.
ARTIFICIAL INTELLIGENCE REVIEW.
56,
10
(2023)
Prediction of Alzheimer's progression based on multimodal Deep-Learning-based fusion and visual Explainability of time-series data.
INFORMATION FUSION.
92,
1
(2022)
Multilayer dynamic ensemble model for intensive care unit mortality prediction of neonate patients.
JOURNAL OF BIOMEDICAL INFORMATICS.
135,
-
(2022)
Automatic detection of Alzheimer?s disease progression: An efficient information fusion approach with heterogeneous ensemble classifiers.
NEUROCOMPUTING.
512,
-
(2022)
Multitask Deep Learning for Cost-Effective Prediction of Patient's Length of Stay and Readmission State Using Multimodal Physical Activity Sensory Data.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS.
26,
12
(2021)
Large-scale and Robust Code Authorship Identification with Deep Feature Learning.
ACM TRANSACTIONS ON PRIVACY AND SECURITY.
24,
4
(2021)
Robust hybrid deep learning models for Alzheimer's progression detection.
KNOWLEDGE-BASED SYSTEMS.
213,
1
(2021)
Alzheimer's disease progression detection model based on an early fusion of cost-effective multimodal data.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE.
115,
1
(2020)
Multimodal multitask deep learning model for Alzheimer's disease progression detection based on time series data.
NEUROCOMPUTING.
412,
-
(2020)
AUToSen: Deep-Learning-Based Implicit Continuous Authentication Using Smartphone Sensors.
IEEE INTERNET OF THINGS JOURNAL.
7,
6
학술회의논문
(2024)
The Impact of Model Variations on the Robustness of Deep Learning Models in Adversarial Settings.
Silicon Valley Cybersecurity Conference.
미국
(2024)
Unmasking the Vulnerabilities of Deep Learning Models: A Multi-Dimensional Analysis of Adversarial Attacks and Defenses.
Silicon Valley Cybersecurity Conference.
미국
(2022)
Black-box and Target-specific Attack Against Interpretable Deep Learning Systems.
Asia Conference on Computer and Communications Security (ASIA CCS).
일본
(2022)
Depth, Breadth, and Complexity: Ways to Attack and Defend Deep Learning Models.
Asia Conference on Computer and Communications Security (ASIA CCS).
일본
(2022)
Leveraging Spectral Representations of Control Flow Graphs for Efficient Analysis of Windows Malware.
Asia Conference on Computer and Communications Security (ASIA CCS '22).
일본
(2022)
MLxPack: Investigating the Effects of Packers on ML-based Malware Detection Systems Using Static and Dynamic Traits.
Asia CCS Workshop on Cybersecurity and Social Sciences (CySSS '22).
일본
(2021)
AdvEdge: Optimizing Adversarial Perturbations Against Interpretable Deep Learning.
The 10th Int conf on Computational Data and Social Networks (CSoNet'21).
캐나다
(2020)
Alzheimer Disease Prediction Model Based on Decision Fusion of CNN-BiLSTM Deep Neural Networks.
Intelligent Systems and Applications (IntelliSys 2020).
네덜란드
(2020)
Multi-χ: Identifying Multiple Authors from Source Code Files.
The 20th Privacy Enhancing Technologies Symposium (PETS2020).
캐나다
발전기금
