Seung Ho Na

Seung Ho Na

PhD Candidate @ KAIST NSS Lab

About Me

I am a PhD candidate at KAIST NSS Lab, advised by Professor Seungwon Shin. I received my master's and bachelor's degree in electrical engineering from KAIST. My research interests lie in the application of machine learning in cybersafety and scrutinizing its effects on cybersecurity. Privacy of individual clients in AI has been one of my focuses in research, and I am expanding my reach to understand the more imminent threats on the individual posed by the Web (e.g., malicious bots).

Having grown up in both South Korea and the US, I had the opportunity to experience both cultures as a student, resulting in bilingual proficiency and a playlist curation that ranges from Bruno Mars to BTS. In terms of programming languages I'm more versatile; my main programming languages (used in research) are Python, C, and Matlab and have adequate experience (e.g., projects, coursework) with Java, Scala, SQL, and Javascript.

If you are interested in working together, feel free to drop an email at any time!

Research

When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs

Hanna Kim, Minkyoo Song, Seung Ho Na, Seungwon Shin, Kimin Lee

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Obliviate: Neutralizing Task-agnostic Backdoors within the Parameter-efficient Fine-tuning Paradigm

Jaehan Kim, Minkyoo Song, Seung Ho Na, Seungwon Shin

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CENSor: Detecting Illicit Bitcoin Operation via GCN-based Hyperedge Classification

Suyeol Lee, Jaehan Kim, Minjae Seo, Seung Ho Na, Seungwon Shin, Jinwoo Kim

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Evolving Bots: The New Generation of Comment Bots and their Underlying Scam Campaigns in YouTube

Seung Ho Na , Sumin Cho, Seungwon Shin

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Witnessing Erosion of Membership Inference Defenses: Understanding Effects of Data Drift in Membership Privacy

Seung Ho Na , Kwanwoo Kim, Seungwon Shin

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Closing the Loophole: Rethinking Reconstruction Attacks in Federated Learning from a Privacy Standpoint

Seung Ho Na , Hyeong Gwon Hong, Junmo Kim, Seungwon Shin

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Reconfigurable Regular Expression Matching Architecture for Real-time Pattern Update and Payload Inspection

Jaehyun Nam, Seung Ho Na, Seungwon Shin, Taejune Park

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Meta-Path-based Fake News Detection Leveraging Multi-level Social Context Information

Jian Cui, Kwanwoo Kim, Seung Ho Na, Seungwon Shin

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Reinhardt: Real-time Reconfigurable Hardware Architecture for Regular Expression Matching in DPI

Taejune park, Jaehyun Nam, Seung Ho Na, Jaewoong Chung, Seungwon Shin

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[Poster] Knowledge Seeking on The Shadow Brokers

Seung Ho Na*, Kwanwoo Kim*, Seungwon Shin

*:Equally Contributed

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Experience

Worked as an intern in the research team. Was assigned a project on using deep learning for anomaly detection of faulty factory components, where I developed a hierarchical classification system that helped decrease false negative samples.

As an engineering student intern at a venture capital company, I had more familiarity in technology industries and conducted market research on IoT and renewable energy.

Education

Under Professor Seungwon Shin, I was able to utilize my AI knowledge and apply it to CTI (cyber threat information) research. My Master’s thesis is research on a knowledge-powered cross-domain investigation of cyber-extortion operators. This work presents an analysis of Clop, a ransomware campaign, using a devised investigation framework that utilizes information from multiple domains.

During my time at KAIST I dedicated much of my time in exploring what I wanted to do in life. After a broad selection of courses from various fields, several undergraduate research programs, and extracurricular activities, I found that learning and discovering new knowledge was what I enjoyed and decided to continue this in graduate school.

Awards

제 5회 금융보안원 논문 공모전 최우수상

제 4회 금융보안원 논문 공모전 대상

A Little More About Me

Alongside my interests in AI and cybersafety, some of my other interests and hobbies are:

  • Watching and playing football; fan of Manchester City F.C.
  • Occasional gaming (TFT, FIFA, and Pokemon Go)
  • Exercising