Match tier
Likely match
Presence
Current · Arkansas
Last published
2025
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
D
Donghoon Kim
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Assistant Professor
Also affiliated: Samsung (South Korea) (2025); Samsung Pharm (South Korea) (2025)
Faculty Researcher
2 h-index
8 pubs
11 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Donghoon Kim's research focuses on the application of machine learning and advanced computational techniques to address diverse challenges. His work includes developing robust methods for Internet of Things (IoT) malware detection and classification, utilizing opcode category features and histogram entropy representations. He has also investigated poisoning attacks against federated learning in smart energy load forecasting and explored Wi-Fi frame detection using spiking neural networks with memristive synapses. In the agricultural domain, Kim has contributed to automated detection of rice bakanae disease through drone imagery analysis. His other research interests include imputing missing environmental data, such as sea surface temperature observations, using multivariate recurrent neural networks, and analyzing consumer behavior related to health functional foods. Kim has collaborated with researchers at Arkansas State University, including Andrew Booth and Kyungtae Kim.
Metrics
- h-index: 2
- Publications: 8
- Citations: 11
Selected Publications
-
Distributed Secret Protection in Cloud Storage: A Threshold-Based Approach for Nextcloud (2026)
-
ACT: Automated CPS Testing for Open-Source Robotic Platforms (2026)
-
Enhancing deep hashing with graph filters and autoencoder-based embeddings (2026)
-
Empirical Analysis of Security Vulnerabilities in Open Source Software Using Static Analysis Tools (2025)
-
Improving Antimicrobial Resistance (AMR) Phenotype Prediction for Unseen Bacteria through Data Augmentation and Machine Learning (2025)
-
Enhanced Android Malware Detection: Fine-Grained Opcode analysis, Data Augmentation and Zero-Day Evaluation (2025)
-
An Empirical Study: Feasibility of Website Fingerprinting Attacks in Real-Time Environments on V3 Onion Services (2025)
-
Website Fingerprinting Attacks with Advanced Features on Tor Networks (2024)
-
Enhancing Deep Hashing With GCN-Based Models for Efficient Similarity Search (2024)
-
Poster: Advanced Features for Real-Time Website Fingerprinting Attacks on Tor (2024)
-
Analyzing Various Machine Learning Approaches for Detecting Android Malware (2024)
-
Employing Machine Learning for the Prediction of Antimicrobial Resistance (AMR) Phenotypes (2024)
-
Devised Deephashing Models Through Self-Supervised Learning for Image Retrieval (2023)
-
Robust IoT Malware Detection and Classification Using Opcode Category Features on Machine Learning (2023)
-
Evolved IoT Malware Detection using Opcode Category Sequence through Machine Learning (2022)
Collaboration Network
Top Collaborators
Doosung Hwang
Dankook University (KR)
11 shared publications
- Robust IoT Malware Detection and Classification Using Opcode Category Features on Machine Learning
- Histogram Entropy Representation and Prototype Based Machine Learning Approach for Malware Family Classification
- Evolved IoT Malware Detection using Opcode Category Sequence through Machine Learning
- Employing Machine Learning for the Prediction of Antimicrobial Resistance (AMR) Phenotypes
- Enhancing Deep Hashing With GCN-Based Models for Efficient Similarity Search
Showing 5 of 11 shared publications
Sooin Kim
Dankook University (KR)
3 shared publications
- Robust IoT Malware Detection and Classification Using Opcode Category Features on Machine Learning
- Devised Deephashing Models Through Self-Supervised Learning for Image Retrieval
- Enhancing deep hashing with graph filters and autoencoder-based embeddings
Andrew Booth
Arkansas State University
3 shared publications
In database
- Website Fingerprinting Attacks with Advanced Features on Tor Networks
- Poster: Advanced Features for Real-Time Website Fingerprinting Attacks on Tor
- An Empirical Study: Feasibility of Website Fingerprinting Attacks in Real-Time Environments on V3 Onion Services
Dong-Heon Baek
Dankook University (KR)
2 shared publications
- Robust IoT Malware Detection and Classification Using Opcode Category Features on Machine Learning
- Histogram Entropy Representation and Prototype Based Machine Learning Approach for Malware Family Classification
Hyun‐Jong Lee
2 shared publications
- Robust IoT Malware Detection and Classification Using Opcode Category Features on Machine Learning
- Evolved IoT Malware Detection using Opcode Category Sequence through Machine Learning
Wongyum Kim
Korea Development Institute (KR)
2 shared publications
- Enhancing Deep Hashing With GCN-Based Models for Efficient Similarity Search
- Devised Deephashing Models Through Self-Supervised Learning for Image Retrieval
Euijin Choo
University of Alberta (CA)
2 shared publications
- Website Fingerprinting Attacks with Advanced Features on Tor Networks
- Poster: Advanced Features for Real-Time Website Fingerprinting Attacks on Tor
Hokeun Kim
2 shared publications
- Empirical Analysis of Security Vulnerabilities in Open Source Software Using Static Analysis Tools
- ACT: Automated CPS Testing for Open-Source Robotic Platforms
Byunghyun Baek
Vitzro Tech (South Korea) (KR)
1 shared publication
- Histogram Entropy Representation and Prototype Based Machine Learning Approach for Malware Family Classification
Seoungyul Euh
Korean Association for Public Security Administration (KR)
1 shared publication
- Histogram Entropy Representation and Prototype Based Machine Learning Approach for Malware Family Classification
Sung‐Hyun Moon
Dankook University (KR)
1 shared publication
- Evolved IoT Malware Detection using Opcode Category Sequence through Machine Learning
Young-Ho Kim
Vitzro Tech (South Korea) (KR)
1 shared publication
- Evolved IoT Malware Detection using Opcode Category Sequence through Machine Learning
Young-Jin Jeon
1 shared publication
- Devised Deephashing Models Through Self-Supervised Learning for Image Retrieval
Se‐Ran Jun
University of Arkansas for Medical Sciences
1 shared publication
In database
- Employing Machine Learning for the Prediction of Antimicrobial Resistance (AMR) Phenotypes
Kyler Dickey
Arkansas State University
1 shared publication
In database
- Analyzing Various Machine Learning Approaches for Detecting Android Malware
Similar Researchers
Based on overlapping research topics
Dakota S. Dale
University of Arkansas at Fayetteville
Machine Learning Applications
Network Security and Intrusion Detection
Remote Sensing in Agriculture
Prasanna Kumar Reddy Mallampati
Southern Arkansas University
Machine Learning Applications
Network Security and Intrusion Detection
Advanced Malware Detection Techniques
Rohan Singh
University of Arkansas at Little Rock
Machine Learning Applications
Network Security and Intrusion Detection
Advanced Malware Detection Techniques
Qinghua Li
University of Arkansas at Little Rock
Machine Learning Applications
Network Security and Intrusion Detection
Advanced Malware Detection Techniques
Kyler Dickey
Arkansas State University
Machine Learning Applications
Network Security and Intrusion Detection
Advanced Malware Detection Techniques
Mohammad Nadim
University of Arkansas at Fayetteville
Machine Learning Applications
Network Security and Intrusion Detection
Remote Sensing in Agriculture