About Me
SeungHun Lee(이승훈)
Network Data Science Lab
Dept. of Computer Science and Engineering
Sangmyung University
Office: C-building 404c
Email: mr.leesh90@gmail.com
Research Interests
- Social Networking Service(e.g., Twitter, Instagram, Pinterest, Yelp)
- Crowdfunding Scam(Deception, Fraud) Detection, Success Prediction
- Network Traffic Classification
- Data Mining, Machine Learning, Deep Learning
- Explainable AI
- NLP(Natural Language Processing)
- Large Language Model(LLM)
Publications
Conferences
Traffic Classification using Deep Learning: High Accuracy is Not Enough
Kanghee Lee, Seunghun Lee, and Hyun-chul Kim
ACM SIGCOMM, New York City, Aug. 2020.(Poster)Content-based Success Prediction of Crowdfunding Campaigns: A Deep Learning Approach
Seunghun Lee, Kanghee Lee, and Hyun-chul Kim
ACM CSCW, New York City’s Hudson River (Jersey City), Nov. 2018.(Poster)The Language of Deceivers: Linguistic Features of Crowdfunding Scams
Wafa Shafqat, Seunghun Lee, Sehrish Malik, and Hyun-chul Kim
International World Wide Web conference (WWW), Montreal, Canada, Apr. 2016.(Poster)SNS Map : Location-based SNS data mapping system
Seunghun Lee, Daeyoung Oh, Minhyuk Kang, and Hyun-chul kim
한국컴퓨터종합학술대회(In Proceedings of the Korea Computer Congress(KCC)), Jeju, Korea, June. 2015.
Journal
Backers Beware: Characteristics and Detection of Fraudulent Crowdfunding Campaigns
Seung-hun Lee, Wafa Shafqat, and Hyun-chul Kim
Journal of MDPI Sensors, Volume 22, Number 19, pp. 7677, Oct. 2022.Crowdfunding Scams : The Profiles and Language of Deceivers
Seung-hun Lee, and Hyun-chul Kim
Journal of The Korea Society of Computer and Information, Volume 23, Number 3, pp. 55-62, Mar. 2018.Predicting Success of Crowdfunding Campaigns using Multimedia and Linguistic Features
Kang-hee Lee, Seung-hun Lee, and Hyun-chul Kim
Journal of Korea Multimedia Society, Volume 21, Number 2, pp. 281-288, Feb. 2018.Smart SNS Map: Location-based Social Network Service Data Mapping and Visualization System
Jangho Yoon, Seung-hun Lee, and Hyun-chul Kim
Journal of Korea Multimedia Society, Volume 19, Number 2, pp. 428-435, Feb. 2016.
Projects
- Explainability in Graph Neural Networks for Internet Traffic Classification
(sponsored by the National Research Foundation, Korea) 2023.06 ~ 2025.02 - Research on Virtualization-based 5G Networks and Cyber Threats
(sponsored by National Security Research Institute, Korea) 2023.04~2023.10 - Deep Learning based Internet Traffic Classification: Myths, Realities, and their Explainabilities
(sponsored by the National Research Foundation, Korea) 2022.06 ~ 2023.05 - Multi-modal data-driven Explainable AI systems and the Future of Digital Finance
(sponsored by the National Research Foundataion, Korea) 2019.09 ~ 2022.02 - Towards Explainable AI in Next-Generation Intrusion Detection systems
(sponsored by National Security Research Institute, Korea) 2019.04~2019.10 - Statistics-based Network Behavior Modeling
(sponsored by National Security Research Institute, Korea) 2018.05 ~ 2018.10 - Traffic Measurement in Anonymity Networks
(sponsored by National Security Research Institute, Korea) 2017.04 ~ 2017.10 - Characterization and Automatic Labeling of Malicious Traffic in Control System Networks
(sponsored by National Security Research Institute, Korea) 2017.04 ~ 2017.10 - Network Traffic Classification for Intrusion Detection
(sponsored by National Security Research Institute, Korea) 2015.06 ~ 2015.12
Education
- Ph.D Dept. of Computer Software, Sangmyung (2018.3 ~)
- M.S Dept. of Computer Science and Engineering, Sangmyung. (2015.3 ~ 2017.2)
- B.S Dept. of Computer Science and Engineering, Sangmyung. (2009.3 ~ 2015.)