AI for Security

Anomaly Detection & Deepfake Detection

LLM+RAG solutions for Cybersecurity Applications

Security for AI

Mitigate vulnerabilities of Generative AI Models

Deep feature learning for
computer vision / time series tasks

Image / Video data analysis
with SOTA deep learning models

Join our lab to apply deep learning and deep feature learning to solve real-world cybersecurity challenges.

We welcome motivated students from all backgrounds — including international students — who are passionate about AI-, Data-driven research.

SecAI Lab은 사이버보안 도메인의 복잡한 문제를 해결하기 위해 Deep Feature Learning과 딥러닝 모델 구조의 설계 및 변형을 통한 표현 학습(representation learning) 연구를 수행합니다.

AI 기반 보안 연구에 관심 있는 학생들의 많은 지원을 환영합니다.

SecAI Lab Benefits

May - Paper accepted for The 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (BK21 IF = 1).

February - Joined Hyundai Mobis, Cybersecurity Technology Management Team as Principal Reasearch Engineer.

December- Paper accepted for The 16th Asian Conference on Computer Vision (ACCV2022). (BK21 IF = 1).
January - Paper accepted for The 31th Web Conference formerly known as International World Wide Web Conference (WWW 2022). (BK21 IF = 4).
January - Joined Research Scholarship program from Hyundai Mobis

December - Received Ph.D. student research scholarship from Hyundai MOBIS. (Dec. 2021 ~ Dec. 2022)
April - Our work "Detecting handcrafted facial image manipulations and GAN-generated facial images using Shallow-FakeFaceNet" has been published as a news article in Academic Times.
March - Paper accepted for 36th International Conference on ICT Systems Security and Privacy Protection (IFIP SEC 2021) (BK21 IF = 1).
March - Paper accepted for Elsevier Journal on Applied Soft Computing (ASOC) - Cite Score 2021 = 10.2, SCIE Q1 IF = 6.725.
January - Paper accepted for The 30th Web Conference formerly known as International World Wide Web Conference (WWW 2021). (BK21 IF = 4).

July - Paper accepted for Conference on Information and Knowledge Management (CIKM 2020) (BK21 IF = 3).
April - Paper accepted for Elsevier Journal on Computer & Security (COSE) - Cite Score 2019 = 5.95 , SCIE Q1 IF = 3.06.

November - Paper accepted for The 35th ACM/SIGAPP Symposium On Applied Computing (ACM SAC 2020).
August 2019, Transferred from The State University of New York - Korea (SUNY KOREA) to Sungkyunkwan University.
August 2019, Attended The 25TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska - USA August 2019.
June 2019, Accepted Poster for The 5th Workshop on Mining and Learning from Time Series (MiLeTS 2019) co-located with the 25TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019).
June 2019, Accepted Poster for TMEDSC 2019: Workshop on Tensor Methods for Emerging Data Science Challenges at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019).
April 2019, Accepted paper for ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2019 (IF = 4).
April 2019, Attended The 34th ACM/SIGAPP Symposium on Applied Computing (ACM SAC 2019), Limassol, Cyprus April 2019.

December 2018, Accepted paper for ACM SIGAPP Symposium on Applied Computing, SAC 2019 (IF = 1).
July 2018, Shahroz Tariq, Sangyup, Lee Hoyoung Kim & Youjin Shin, Won the top 7th place (top 3rd among universities) among 400 teams in Korea for AI R&D Challenge on Fake Face Image Detection.
December 2017, Sangyup Lee, Shahroz Tariq & Homin, Won the 2nd place at National Data Science Challenge (http://challenge.cisc.or.kr/), (Media coverage click here).

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