I am an AI engineer and researcher based in South Korea, working at the intersection of AI Security, Multi-Agent Systems, Computer Vision, and scalable AI-driven software systems.
My work focuses on building practical AI systems beyond research prototypes — from side-channel attack analysis and abnormal behavior detection to AI-assisted review analysis and full-stack AI services.
Research on deep learning-based side-channel attacks, hiding techniques, feature engineering, and simulated IoT/CPS environments for AI security evaluation.
Building abnormal behavior detection systems using CCTV/security camera datasets and ensemble-based AI verification models.
Developing AI-connected web systems using React, Node.js, SQLite, JSON APIs, and deployment-ready Docker environments.
Dockerized AI environments, workflow automation, dataset generation pipelines, GPU-based experiments, and reproducible AI systems.
Research project focused on evaluating deep learning-based side-channel attacks in simulated embedded and IoT environments.
This work includes dataset generation, power trace extraction, feature engineering, and ensemble-based model validation using simulated ARM Cortex-M4 systems.
Python · PyTorch · QEMU · GDB · Docker · CPS Security · IoT Security · Side-Channel Analysis
AI verification project using CCTV/security camera datasets for abnormal behavior detection in residential and public spaces.
The project focuses on ensemble-based validation using C3D, CNN_RNN, and SVM models, alongside Docker-based deployment environments for reproducible execution.
Computer Vision · PyTorch · CCTV Analysis · Abnormal Detection · Docker · Ensemble Models
Evaluating the Vulnerability of Hiding Techniques in Cyber-Physical Systems Against Deep Learning-Based Side-Channel Attacks
- Applied Sciences
- Second Author
- Published (2025.06)
Enhancing Deep Learning-Based Side-Channel Analysis Using Feature Engineering in a Fully Simulated IoT System
- Expert Systems with Applications
- Second Author
- Published (2025.03)
A Study on the Criminal Information Collection and Classification System for Drug Trafficking Under the Dark Web
- MITA (Multimedia Information Technology and Applications)
- First Author
- Published
- 멀티미디어학회
- Co-Author
- Published
- 스마트 치안학회
- First Author
- Published
- 지능시스템학회
- First Author
- Published
- 멀티미디어학회
- First Author
- Published
- 스마트 치안학회
- First Author
- Published
- 멀티미디어학회
- First Author
- Published (2021.10)
Python · PyTorch · TensorFlow · CNN · C3D · CNN_RNN · Computer Vision · Side-Channel Analysis
IoT Security · CPS Security · Feature Engineering · Static Analysis · Vulnerability Detection
JavaScript · Node.js · SQLite
Git · GitHub · Docker · Linux · QEMU · GDB
- Building scalable Multi-Agent and LLM-based AI systems
- Researching practical AI security techniques against side-channel attacks
- Expanding AI engineering projects for real-world deployment
- Developing AI-driven automation and workflow systems
- Strengthening production-level AI + Backend integration skills
- AI Security
- Side-Channel Analysis
- Computer Vision
- CPS / IoT Security
- AI-assisted Security Systems
- Real-world AI Deployment
- Korean — Native
- English — Professional Working Proficiency
- GitHub: https://github.com/mu9029
- Email: mu9029@dgu.ac.kr
I am interested in opportunities involving AI Engineering, AI Security Research, Multi-Agent Systems, Computer Vision, and Full-Stack AI development — especially in teams building practical AI systems with real-world impact.