Insup Lee
AI & Security Researcher @ UAE and Korea
Ph.D. Candidate @ Korea University

I am an AI & Security Researcher based in both the UAE and South Korea. My research primarily focuses on AI-based security, generative models, network & wireless security, threat intelligence, and side-channel analysis.

My approach to security research is built on five years of experience at the Agency for Defense Development (ADD), as well as international joint projects with the UAE Ministry of Defense.

As a Ph.D. candidate in Cybersecurity at Korea University, I have mainly explored how generative models can improve cybersecurity. For my next steps, I plan to investigate the flip side: uncovering the inherent vulnerabilities within LLMs and agentic AI systems.

CV / Email / LinkedIn / Google Scholar/ ORCiD

News
Research Interests
  • AI for Cybersecurity: cyber threat intelligence using NLP/LLM, hardware security (side-channel analysis), adversarial ML
  • Network and Wireless Security: drones, robust communications, network intrusion detection systems, anomaly detection
  • Generative Models: diffusion transformers and GANs for data augmentation, LLM for software vulnerability detection
Education
  • Ph.D. Candidate in Cybersecurity, Korea University, Seoul, Republic of Korea, 2019 - Present
    • Title: Domain-Specific Generative Models for Data Augmentation in Multi-Layer Cybersecurity
    • Advisors: Sangjin Lee and Seokhie Hong
  • B.E. in Cyber Defense, Korea University, Seoul, Republic of Korea, 2014 - 2018
Employment History
  • Lecturer, Korea University, Seoul, Republic of Korea, 2025.9 - 2026.2
    • Taught graduate-level course "Computer Networks (SCS 302)"
  • Research Intern, Indiana University, Bloomington, Indiana, USA, 2025.3 - 2025.6
    • Researched quantification methods for ML security in autonomous vehicle systems
  • Security Engineer, Ministry of National Defense, Republic of Korea, 2023.8 - 2025.5
    • Led international joint research on AI-based security with the UAE Ministry of Defense
      "AI-Based RF Signal Analysis for Drone Security" (resulting in publication [J6])
    • Taught cybersecurity courses "Penetration Testing" in English to UAE officers
  • Researcher, Agency for Defense Development (ADD), Seoul, Republic of Korea, 2018.7 - 2023.7
    • Conducted AI-based security research and in-house software development (Advisor: Changhee Choi)
      (1) "Detection of Nation-Sponsored Cyber Attacks Using NLP Technologies" (Apr 2021 - Jul 2023)
      (2) "Generative Models for Cybersecurity Data Augmentation" (Jun 2019 - Oct 2020)
      (3) "IPADS: Integrated Proactive and Adaptive Defense Systems" (Aug 2018 - May 2019)
    • Published six international papers [C1, C2, J1, J2, J3, J5], four patents, and 12 domestic papers
Publications
(C: conference / J: journal)
International Publications
[C3] Exploiting Per-Core Leakage: Electromagnetic Side-Channel Monitoring of Multicore Architectures
D. Bae, S. Park, I. Lee, Y. Jung, K. Lee, H. Kim, and S. Hong
ACM/IEEE Design Automation Conference (DAC) 2026 [paper]
(Acceptance Rate: XX.X%=XX/XX; BK21+ IF: 3)
[J8] 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)
[J7] 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)
[J6] 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)
[J5] 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)
[J4] 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)
[J3] 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)
[J2] 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)
[J1] 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)
[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]
[C1] Opcode Sequence Amplifier Using Sequence Generative Adversarial Networks
C. Choi, S. Shin, and I. Lee
International Conference on ICT Convergence (ICTC) 2019 [paper]
Domestic Publications (Korean)
  • 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.
Patents
  • 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.
  • 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.
  • 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.
  • 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.
Awards & Honors
  • KU Graduate School Achievement Award, February 2026 [link|pdf]
    Korea University, Seoul, Republic of Korea
  • Certificate of Commendation, UAE-ROK Engagement Program, March 2025 [pdf]
    United Arab Emirates Ministry of Defense
  • UAE Ambassador’s Commendation, March 2025 [pdf]
    Embassy of the Republic of Korea to the United Arab Emirates
  • Full Tuition Scholarship, Korea University, 2014 - 2018
    Ministry of National Defense, Republic of Korea
Other Experience
  • AI Cyber Challenge (AIxCC), DARPA and ARPA-H, USA, 2024.4 - 2024.8
    • Participated in the semifinal round as a member of Team KORIA, submitting our cyber reasoning system that leverages LLMs for automated detection and patching of software vulnerabilities
  • SW Outsourcing Development, KCMVP-Certified Cryptographic Module, 2017.6 - 2018.3
    • Implemented a cryptographic module with 25,000 LoC in C - ARIA block cipher (modes: ECB, CBC, CTR), hash functions (SHA-256, SHA-512), and HMAC-based DRBG for Windows (.dll) and Linux (.so)
Technical Skills
  • AI & Deep Learning: Generative models (diffusion transformers, GANs), LLM pipelines, Adversarial robustness
  • Cybersecurity: Side-channel analysis, CTI (TTP extraction, attribution), Cryptographic engineering (25k+ LoC)
  • Languages & Tools: Python, C/C++, CUDA, PyTorch, Linux, Git, Docker, Streamlit
Professional Activities
  • Reviewer, IEEE Transaction on Dependable and Secure Computing (TDSC), 2025
  • Reviewer, IEEE Transactions on Information Forensics and Security (TIFS), 2026
  • Reviewer, IEEE Transaction on Communications (TCOM), 2025, 2026
  • Reviewer, IEEE Journal on Selected Areas in Communications (JSAC), 2025, 2026
Teaching Experience
  • Lecturer, Fall 2025: Computer Networks (SCS302), Korea University

Last Update: March 2026