Publications
Under Review
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Multi-Domain Side-Channel Analysis for Anomaly Detection in Embedded System
S. Park, D. Bae, I. Lee, J. Kim, H. Oh, H. Kim, and S. Hong
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(Blind Review)
J. Baek, G. Ahn, S. Park, D. Bae, G. Kim, I. Lee, H. Kim, and S. Hong
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(Blind Review)
D. Bae, S. Park, I. Lee, Y. Jung, K. Lee, H. Kim, and S. Hong
International Journals & Conferences
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[J9] LeakDiT: Diffusion Transformers for Trace-Augmented Side-Channel Analysis
I. Lee, D. Bae, S. Hong, and S. Lee
IEEE Computer Architecture Letters 2026 [Paper]
(SCI 2024 Top 79.2% in Computer Science, Hardware & Architecture)
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[J8] Multi-Step LLM Pipeline for Enhancing TTP Extraction in Cyber Threat Intelligence
H. Kim, D. Lee, I. Lee, S. Lee, and S. Lee
IEEE Access 2025 [Paper]
(SCI 2024 Top 34.8% in Engineering, Electrical & Electronic)
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[J7] Enhancing Modulation Classification via Diffusion Transformers for Drone Video Signal Processing
I. Lee, K. Alteneiji, and M. Alghfeli
IEEE Signal Processing Letters 2025 [Paper]
(SCI 2024 Top 31.6% in Engineering, Electrical & Electronic)
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[J6] MuCamp: Generating Cyber Campaign Variants via TTP Synonym Replacement for Group Attribution
I. Lee and C. Choi
IEEE Transactions on Information Forensics and Security (TIFS) 2025
[Paper]
(SCI 2024 I/F Top 7.8% in Computer Science, Theory & Methods)
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[J5] UniQGAN: Towards Improved Modulation Classification With Adversarial Robustness Using Scalable Generator Design
I. Lee and W. Lee
IEEE Transactions on Dependable and Secure Computing (TDSC) 2024
[Paper]
(SCI 2023 I/F Top 4.9% in Computer Science, Software Engineering)
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[J4] Camp2Vec: Embedding Cyber Campaign With ATT&CK Framework for Attack Group Analysis
I. Lee and C. Choi
ICT Express 2023
[Paper]
(SCI 2023 Top 23.0% in Computer Science, Information Systems)
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[J3] Exploiting TTP Co-occurence via GloVe-Based Embedding With ATT&CK Framework
C. Shin, I. Lee, and C. Choi
IEEE Access 2023
[Paper]
(SCI 2023 Top 34.4% in Engineering, Electrical & Electronic)
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[J2] BAN: Predicting APT Attack Based on Bayesian Network With MITRE ATT&CK Framework
Y. Kim, I. Lee, H. Kwon, G. Lee, and J. Yoon
IEEE Access 2023
[Paper]
(SCI 2023 Top 34.4% in Engineering, Electrical & Electronic)
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[J1] UniQGAN: Unified Generative Adversarial Networks for Augmented Modulation Classification
I. Lee and W. Lee
IEEE Communications Letters 2022
[Paper]
(SCI 2023 Top 33.2% in Telecommunications)
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[C3] Encrypted Malware Traffic Detection Using Incremental Learning
I. Lee, H. Roh, and W. Lee
IEEE INFOCOM - Poster Session 2020
[Paper]
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[C2] Anomaly Dataset Augmentation Using Sequence Generative Models
S. Shin, I. Lee, and C. Choi
IEEE International Conference on Machine Learning and Applications (ICMLA) 2019
[Paper]
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[C1] Opcode Sequence Amplifier Using Sequence Generative Adversarial Networks
C. Choi, S. Shin, and I. Lee
International Conference on ICT Convergence (ICTC) 2019
[Paper]
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Patents
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Method for Augmentating Cyber Attack Campaign Data to Identify Attack Group, and Security System Performing Same
C. Choi and I. Lee
Korea Patent Application Number. 10-2024-0176082, December 2, 2024.
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Information Identification Method and Electronic Apparatus Thereof
C. Choi, I. Lee, C. Shin, and S. Lee
Korea Patent Application Number. 10-2024-0006106, January 15, 2024.
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Method for Training Attack Prediction Model and Device Therefor
C. Choi, C. Shin, S. Shin, S. Seo, and I. Lee
U.S. Patent Number. US20230308462A1, September 28, 2023.
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Appratus, Method, Computer-readable Storage Medium and Computer Program for Generating Operation Code
C. Choi, S. Shin, and I. Lee
Korea Patent Number. 10-2246797, April 30, 2021.
Domestic Journals & Conferences
- S. Park, D. Bae, I. Lee, H. Kim, and S. Hong, “EM-Based Anomaly Detection using a Dual-Domain Approach,” in Proc. of the KIISC Winter Conference (CISC-W), Nov. 2025. (Selected as an Outstanding Paper Award)
- J. Kim, I. Lee, C. Jeon, S. Kim, S. Hong, and S. Lee, “Reinforcement Learning for Parameter Optimization in CADO-NFS Polynomial Selection,” in Proc. of the KIISC Winter Conference (CISC-W), Nov. 2025.
- S. Park, D. Bae, I. Lee, H. Kim, and S. Hong, “A Statistical Time-Domain Approach to Anomaly Detection for Robotic-Arm MCU,” in Proc. of the KIMST Fall Conference, Nov. 2025.
- H. Park and I. Lee, “Enhanced DDoS Detection via Traffic Volume-Based Labeling and Transfer Learning,” Journal of Internet Computing and Services (JICS), vol. 26, no. 4, pp. 1-8, Aug. 2025.
- K. Kim and I. Lee, “User Behavior Embedding via TF-IDF-BVC for Web Shell Detection,” Journal of The Korea Institute of Information Security & Cryptology (JKIISC), vol. 34, no. 6, pp. 1231-1238, Dec. 2024.
- I. Lee, C. Shin, and C. Choi, “Mutating Cyber Camapaign With TTP Word Replacement,” in Proc. of the KIMST Annual Conference, Jun. 2023.
- C. Shin, I. Lee, and C. Choi, “Towards GloVe-Based TTP Embedding With ATT&CK Framework,” in Proc. of the KIMST Annual Conference, Jun. 2023.
- C. Choi, I. Lee, C. Shin, and S. Lee, “Cyber Threat Campaign Analysis Based on PEGASUS and RoBERTa Model,” in Proc. of the KIMST Annual Conference, Jun. 2023.
- I. Lee, C. Shin, S. Shin, S. Seo, and C. Choi, “Analyzing Cyberattack Campaign Similarity via TTP Sequence Embedding,” in Proc. of the KIMST Annual Conference, Jun. 2022.
- S. Shin, I. Lee, C. Shin, S. Seo, and C. Choi, “Cyber Campaign Analysis With TTP Embedding Using TF-IDF,” in Proc. of the KIMST Annual Conference, Jun. 2022.
- C. Shin, S. Shin, I. Lee, S. Seo, and C. Choi, “Classifying TTP Based on CIA Labeling,” in Proc. of the KIMST Annual Conference, Jun. 2022.
- C. Choi, C. Shin, S. Shin, S. Seo, and I. Lee, “Cyber Attack Group Classification Using Siamese LSTM,” in Proc. of the KIMST Annual Conference, Jun. 2022.
- C. Shin, S. Shin, S. Seo, I. Lee, and C. Choi, “Embedding and Training RNN to Estimating the Goal of Cyber Attack,” in Proc. of the KIMST Fall Conference, Nov. 2021.
- S. Shin, C. Shin, S. Seo, I. Lee, and C. Choi, “The Proposed Approach for Country Prediction With TTP-based Cyber Data Using GCN,” in Proc. of the KIMST Fall Conference, Nov. 2021.
- C. Choi, C. Shin, S. Shin, S. Seo, and I. Lee, “Deep Learning for Estimating Next Action of Cyber Attack,” in Proc. of the KIMST Fall Conference, Nov. 2021.
- Y. Park, S. Shin, and I. Lee, “A Study on Evaluation Method of NIDS Datasets in Closed Military Network,” Journal of Internet Computing and Services (JICS), vol. 21, no. 2, pp. 121-130, Apr. 2020.
- I. Lee, J. Kim, and J. Park, “Analysis of Weight Setting in Incremental Learning to Improve Real-Time Intrusion Detection,” in Proc. of the KIMST Annual Conference, Jun. 2019.
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