M.S. Student @ National Taiwan UniversityI am a first-year Master student in Computer Science at National Taiwan University. My passion for CS and mathematics was ignited through independent software development projects, which ultimately inspired my self-motivated career transition from dentistry to computer science.
My research focuses on Algorithmic Machine Learning, Convex Optimization, and Spectral Graph Theory, with current emphasis on efficient algorithms for large-scale optimization and graph neural networks.
I have published research in network steganography and possess strong mathematical intuition and theoretical foundations. I am actively seeking summer research internships in algorithmic ML and optimization.
Warning
Problem: The current name of your GitHub Pages repository ("Solution: Please consider renaming the repository to "
http://".
However, if the current repository name is intended, you can ignore this message by removing "{% include widgets/debug_repo_name.html %}" in index.html.
Action required
Problem: The current root path of this site is "baseurl ("_config.yml.
Solution: Please set the
baseurl in _config.yml to "Education
-
National Taiwan UniversityDepartment of Computer Science and Information Engineering
M.S. Student2024 - present -
National Defense Medical CenterB.S. in Dentistry2018 - 2024
Experience
-
Automated Gaming Infrastructure ProjectBackend Engineer & Algorithm Developer2022 - 2023
Selected Publications (view all )
The Obfuscated Network Steganography
Da-Chih Lin, Shang-Yu Chou
IEEE AccessIn Press. 2025
Network header steganography hides data in network headers instead of payloads. Traditional single-channel methods are vulnerable to statistical detection like chi-square tests. We present an enhanced algorithm using BCH code redundant bits to evade detection. A Peterson-Gorenstein-Zierler decoder recovers the data reliably. Our method achieves 80% higher security than existing techniques, significantly improving covert communication in network systems.
The Obfuscated Network Steganography
Da-Chih Lin, Shang-Yu Chou
IEEE AccessIn Press. 2025
Network header steganography hides data in network headers instead of payloads. Traditional single-channel methods are vulnerable to statistical detection like chi-square tests. We present an enhanced algorithm using BCH code redundant bits to evade detection. A Peterson-Gorenstein-Zierler decoder recovers the data reliably. Our method achieves 80% higher security than existing techniques, significantly improving covert communication in network systems.