사업단소식 게시판목록 | Enterprise Organization of National Program of Excellence in Software

[Jan 29, 2026] AXIS Research Lab Wins the Creative Award Grand Prize at HCIK 2026

AXIS Research Lab Wins the Creative Award Grand Prize at HCIK 2026 The AXIS research team (Gahee Kim, Yujung Kim, Yebom Choi) participated in the Korean Institute of Information Scientists and Engineers academic conference HCI Korea 2026, held in Hongcheon, Gangwon-do from January 26 to 28, and won the Grand Prize in the Creative Award category. Celebrating its 20th anniversary this year, HCI Korea is the largest domestic event in the field of Human-Computer Interaction (HCI). The AXIS research team presented Phodong, a phygital fairy tale creation platform that combines object recognition vision technology with generative AI, in the Creative Award category. From Passive Consumption to a Space for Creative PlayThe award-winning work 'Phodong' is an interactive service designed to solve the problem of children's passive digital media consumption and alleviate the burden of parenting. Utilizing an object recognition vision system with an asynchronous processing structure, the research team implemented technology where AI recognizes physical objects children see and feel in their daily lives in real-time and transforms them into engaging narrative characters. Through this, they proposed a Joint Media Engagement (JME) model where parents and children create stories together. While existing children's content was limited to one-sided audiovisual stimulation, Phodong received high marks from the judges for inducing active exploration and expanding creativity by using real-world objects as materials for play. Focus of Attention on Site, Recognition for Technical Completion and Emotional Value During the Creative Award exhibition period, the AXIS research team's booth was a space for experience where technical innovation and warm sensitivity coexisted. Visitors personally demonstrated the prototype version of Phodong and experienced the process of ordinary objects turning into protagonists in a fairy tale. On-site attendees showed positive reactions, stating, "It showed that AI technology can be a warm medium that connects conversations between family members rather than just a cold computational tool." In particular, professional researchers in the HCI field paid attention to the technical implementation and service completeness in generating custom personas suitable for a child's eye level in real-time through LLM (Large Language Model) prompt engineering. A Leap Forward as Next-Generation HCI Talent Through this award, the AXIS Research Lab proved its next-generation research capabilities in fusing technology with humanistic values. Beyond laboratory experiments, the students enhanced the service by communicating with users at the actual conference site, resulting in the Grand Prize at the Creative Award. Furthermore, various research labs from our school, including the AXIS Research Lab, actively participated in this event. A meaningful time for academic harmony was prepared as junior students who visited through the School of Convergence undergraduate observation program congratulated the achievements together. The Phodong research team shared their ambition, stating, "We will continue to conduct warm HCI research where technology can bring positive changes to human life." Research Title and Participating Researchers - Phodong: A Platform for Elaborating Children's Narrative Play and Promoting Parent-Child Co-creation Using Object Recognition Vision Systems - Gahee Kim (Department of Immersive Media Engineering, Graduate School, College of Computing and Informatics), Yujung Kim (Culture & Technology Convergence Major, School of Convergence), Yebom Choi (Department of Interaction Science, Graduate School, College of Computing and Informatics)
- 작성일 2026-01-29
- 조회수 215
[Jan 22, 2026] Professor Jaekwang Kim main Lab., a paper accepted for 2026 ACM Web Conference (WWW) Research Track

A paper from main Lab. (Advisor: Professor Jaekwang Kim) has been accepted for publication in the top-tier international conference, The 2026 ACM Web Conference (WWW) Research Track. The paper is scheduled to be presented in Dubai in April 2026. The paper titled "FCRLLM: Aligning LLM with Collaborative Filtering for Long-tailed Sequential Recommendation" involved Byung-moon Heo (PhD student, Artificial Intelligence Convergence Major), Nam-jun Lee (Master's student, Artificial Intelligence Convergence Major), and Seon-a Kim (Master's student, Department of Computer Science and Engineering) as authors, with Professor Jaekwang Kim participating as the corresponding author. To address recommendation challenges for long-tailed users and items with insufficient interaction data, this research proposes the FCRLLM framework, which combines the rich semantic knowledge of Large Language Models (LLMs) with traditional collaborative filtering signals. The core technology, the Flipped Classroom mechanism, encourages dynamic alignment by allowing collaborative representations and semantic representations to interchangeably serve as teacher and student. During this process, a Hopfield Network-based energy function is used to minimize the differences in attention patterns between the two modalities, enabling complementary learning. The proposed method was evaluated through experiments on three real-world datasets, showing that it consistently improves recommendation performance regardless of item popularity or user activity levels. This study indicates that integrating multi-dimensional information through a bidirectional teacher-student structure allows for the development of more sophisticated and diverse recommendation systems. | Professor Jaekwang Kim | linux@skku.edu | main Lab. | sites.google.com/view/skku-milab
- 작성일 2026-01-22
- 조회수 307
[Jan 22, 2026] Professor Simon Sungil Woo, Department of Computer Science and Engineering: A Researcher Safeguarding Soc

Along with the advancement of generative AI, the issue of deepfakes exploited through AI is becoming increasingly serious. Professor Simon Sungil Woo, who is affiliated with the Department of Computer Science and Engineering, the Graduate School of Artificial Intelligence, and the Data Science Convergence Major at our university, is responding to this social trend through deepfake detection research. He is revealing his prominence in the field, ranking 8th globally in the deepfake category according to Google Scholar. Contrary to the past notion that technology is limited to academic research, the technology demonstrated by Professor Simon Sungil Woo serves as the core key to solving practical problems. In this 579th People Focus, we listen in detail to his philosophy as an artificial intelligence researcher and educator, and raise the question of what direction technology should be researched in. | Hello, Professor. Please introduce yourself briefly. I am Simon Sungil Woo, currently affiliated with the Department of Computer Science and Engineering, the Graduate School of Artificial Intelligence, and the Data Science Convergence Major at Sungkyunkwan University. Since arriving at Sungkyunkwan University in 2019, I have been diligently conducting research related to artificial intelligence security, particularly deepfake detection. I immigrated to the United States during my senior year of high school and lived there before returning to Korea. Before returning to Korea, I worked as a researcher at the NASA Jet Propulsion Laboratory for about nine years. As I continued my career, I felt the need to study more and started my doctoral program late, but looking back now, I think it was the greatest investment of my life with no regrets. Currently, I am spending busy yet happy days being able to share new knowledge with students and conduct the research and work I want to do. ▲ (From left) Professor Simon Sungil Woo, OpenAI founder Sam Altman | You recently received a Minister's Citation from the Ministry of Science and ICT for your research on deepfake detection technology. Could you explain that research in detail? I have been conducting research related to deepfake detection since 2017. In the past, instances of deepfakes and the misuse of artificial intelligence were not considered major social problems, but with the development of generative AI technology, they are becoming increasingly significant issues. It is regrettable that cases of AI misuse in many fields, such as information manipulation, fake news, and non-consensual sexual imagery of acquaintances, are increasing over time. To solve this, I am researching detection technology with high robustness and generalization performance that can detect various types of evolving deepfakes with high performance. Currently, I am researching deep learning architectures that can detect deepfakes by efficiently learning from large amounts of data. In particular, I am using large deep learning models such as CLIP and DINO to increase the generalization performance of detection. Additionally, I am conducting research to detect deepfakes in various environments, especially low-resolution or compressed ones, by utilizing Knowledge Distillation techniques, where a large and smart model first learns from low-quality models and then transfers that content to a smaller model. Results have been achieved, such as many researchers around the world utilizing the multimodal deepfake dataset (FakeAVCeleb)* that I released for the first time in the world. Also, our team achieved the feat of ranking 2nd in the world at the deepfake detection challenge held at IEEE ICCV, a world-renowned computer vision academic conference, in October 2025. *Multimodal deepfake dataset (FakeAVCeleb): Core data for detecting more realistic deepfake attacks, including data where voice and video are manipulated simultaneously. Based on the research achievements accumulated over a long period, I am confident that our research team is the best in the field of domestic deepfake detection technology. I believe I received this Minister's Award because these research achievements, along with my efforts to prevent the misuse of deepfakes and contribute to solving social problems, were highly evaluated. | I understand that your research team does not stop at research but is contributing to solving deepfake issues by cooperating with various organizations such as the Korean National Police Agency. How is this collaboration actually taking place, and could you introduce any achievements? In the past, we conducted joint research with the National Forensic Service, Samsung SDS, the Korean National Police Agency, and the Supreme Prosecutors' Office. Currently, we are cooperating with the Korean National Police Agency and the National Election Commission. In particular, we are developing technology for the Korean National Police Agency that is easy to use with high accuracy and utility so that investigators can apply it to actual investigations. I am proud to say that this technology is 100% domestic technology and is an image/video deepfake detection method developed at Sungkyunkwan University. Furthermore, through periodic meetings with the Korean National Police Agency, we are continuously improving the model by identifying specific difficulties in investigations and how we can provide more practical help. In addition to the domestic Korean National Police Agency, we are also collaborating with the Dusseldorf Police Department in Germany, and we have turned the detection model we created into an API, which the German police are currently testing and utilizing. Also, in preparation for the local elections in June 2026, we have begun cooperating with the National Election Commission to prevent the misuse of deepfakes in advance. It is personally meaningful that the detection technology we created is contributing to making a better society. | I imagine there were many difficulties while researching a field where technology develops as fast as deepfakes. I am curious about the obstacles you faced during the research process and how you have overcome them. AI technology is evolving very rapidly. In particular, generative AI technology is being applied to deepfakes and is being widely misused. In other words, when a new deepfake technique that was not used in the training data emerges, a problem arises where the performance of existing models drops significantly. Therefore, the process of continuously collecting new data, training models, and creating new models is an obstacle. To solve this, we are improving detection performance by applying Continual Learning, Domain Adaptation Methods utilized in machine learning, and various Data Augmentation techniques and high-performance face recognition techniques. Also, we are updating the model to continuously increase detection performance by utilizing the tendency of images or voices created by recent generative AI to have repetitive patterns in specific frequency domains. The biggest task at hand is to create a detection method that shows high performance even for deepfakes in the real world, which are difficult to predict. I and our lab are continuing research on detecting deepfakes misused in reality by utilizing the aforementioned technologies. | Among your career highlights, your participation in the Special Photo Exhibition: Immortal Heroes of the June 25 War, Returning as Young Men was impressive. What was the motivation for participating in that exhibition and what was the significance of this project to you as a researcher? ▲ A photo of General Kim Doo-man restored using AI face restoration technology (GFP-GAN) and Face Restoration. Source = Ministry of Patriots and Veterans Affairs By chance, the Ministry of Patriots and Veterans Affairs inquired whether it would be possible to use artificial intelligence technology to restore damaged and faded photos of June 25 heroes in celebration of the 70th anniversary of the end of the June 25 War. It was such a meaningful task that the students and I were happy to participate. As a researcher, it was a project I was very happy to carry out as it became an opportunity for the technologies we developed to respond, even if only a little, to the hard work and sacrifice of the heroes who nobly gave their lives for the country. Also, it seems the reward was even greater because the restored photos were able to bring great joy to the bereaved families, as shown below. -Words from a bereaved family member of a June 25 hero in a photo restored at the time-" I am immensely grateful to the students of the Department of Computer Science and Engineering and the Graduate School of Artificial Intelligence. In particular, Professor Simon Sungil Woo, you worked so hard. I tried to find a way to convey my gratitude but couldn't, so I am leaving words of thanks here to express my appreciation. (Omitted) Last March, the Ministry of Patriots and Veterans Affairs and the students of the Department of Computer Science and Engineering and the Graduate School of Artificial Intelligence worked with blood, sweat, and tears to restore the only remaining photo in the world so naturally, prettily, and beautifully. Only one photo remained from my father's days as a student in the 8th class of the Korea Military Academy 70 years ago, which had faded, and it was barely sent home after requesting it from the academy's civil service office. That one photo of my father who died in battle is my number one precious treasure that cannot be exchanged for money or anything else. I am beyond grateful that you restored such a photo into a natural color photo so vividly. I would like to take this opportunity to express my sincere gratitude and thanks to Sungkyunkwan University and the students who worked so hard." >Go to see the article related to the project | Looking at your research, there is a common significance of solving social problems through technology. What are the criteria or values you prioritize most when deciding on a research topic? The criteria I use to decide on a research topic are as follows. 1. Can the technology be helpful to society beyond economic value? 2. Is it a technology that is meaningful and can truly help people? 3. Is it a topic that researchers, including myself, can enjoy researching? 4. Is it a new field that has not been researched much before? 5. Is it a technology that will be essential in the future? Academic value is important, but at the same time, I believe it is necessary to develop technology that fundamentally helps people and further helps society as a whole. In particular, we can see even now that human and social values can be fluctuated and damaged by the development of artificial intelligence. Also, I am very worried as the harms and risks of artificial intelligence are increasing. Therefore, as a researcher and engineer, I have a great interest in and prepare for research and development of artificial intelligence that can contribute to society while encompassing human values. | You also have experience working as a researcher at the NASA Jet Propulsion Laboratory. Please introduce any memorable episodes or experiences from that process that influenced your current research. The Mars Reconnaissance Orbiter (MRO)* research I participated in in 2005 was my first space mission project. I researched and developed the CFDP file transfer protocol and DTN (Delay-Tolerant Networking) that transmit photo files taken on Mars to Earth. It seems truly amazing that the satellite I participated in developing went to Mars and that it is still operating today, 20 years later, far exceeding its design life. * Mars Reconnaissance Orbiter (MRO): A spacecraft designed to search for the presence of water on Mars and support Mars exploration missions, providing evidence such as safe landing site selection for Mars landers and additional evidence of water flowing on the Martian surface. ▲ Graphic image of the Mars Reconnaissance Orbiter. Source = NASA Regardless of material value, the fact that I could participate in a project for the development of mankind scientifically was truly a precious experience. It was also a great honor to be able to research with truly outstanding engineers, scientists, and technicians at NASA. Working with them, I learned how to work when multiple people carry out a task together. Currently, I am conducting research that is completely different from what I did at NASA, but the collaboration methods, ways of harmony, approach to research problems, and how to write research papers and proposals that I learned there are providing great help to me in many ways today. | Are there any research fields you would like to newly challenge in the future, or research topics you are currently preparing with interest? I would like to research artificial intelligence security and, as mentioned before, artificial intelligence technology that treasures and respects human values, as well as new artificial intelligence foundation models. | In addition to research activities, you are performing various roles as an educator and lab head. I am curious about what you think a 'good lab' looks like. I believe that in a good lab, all participating researchers must have a sense of responsibility for their assigned tasks, both humanly and professionally. This is a truly important part everywhere as it is a consideration and promise to each other. In any organization, an individual cannot do anything alone, no matter how outstanding they are. It seems that better results come out when individuals gather and create synergy. Therefore, members should respect and be considerate of each other and not be selfish. I hope students think of study and research as an investment in their own future. Since the process is not easy, according to what I have seen, it is not the smart students who succeed, but the students with persistence who work hard that succeed in lab life and society. Therefore, if there are many responsible and persistent students, I believe performance will naturally follow and it will become a good lab on its own. ▲ Professor Simon Sungil Woo restoring photos with students. Source = Electronic Times | Lastly, please say a word to students who are interested in your lab, the DASH Lab. I hope students who want to go a step further beyond artificial intelligence technology that is simply of high interest now and can make a lot of money (e.g., how to increase the performance of LLM?) and research and develop truly meaningful artificial intelligence technology (e.g., how to fundamentally solve the problems of LLM?) will contact me. Also, as mentioned before, I hope students who are kind, responsible, and will research hard, which is necessary to create a good lab, will apply. >Go to read the DASH Lab visit article of Professor Simon Sungil Woo >DASH Lab Homepage
- 작성일 2026-01-22
- 조회수 302
[Jan 12, 2026] Professor Hyungjoon Koo SecAI Lab, a paper accepted for FSE '26

The paper titled "Fool Me If You Can: On the Robustness of Binary Code Similarity Detection Models against Semantics-preserving Transformations," co-authored by Ji-yong Eom (Ph.D. candidate), Min-seok Kim (M.S. candidate), both from the SecAI Lab (supervised by Hyungjoon Koo, https://secai.skku.edu/), and Michalis Polychronakis from Stony Brook University, has been accepted for publication at the prestigious Foundations of Software Engineering 2026 (FSE '26). The paper will be presented in July 2026. Software reverse engineering is a critical process in the security field, including vulnerability analysis and malware detection, but it requires a high level of expertise. However, relying solely on such methods presents limitations in effectively addressing the rapidly increasing modern threats. To overcome this challenge, recent approaches have actively proposed techniques to assist reverse engineering with artificial intelligence, especially models that extract contextual information from machine code (assembly language). Similar to how natural language can convey meaning through context-preserving transformations, assembly language also has techniques for transforming code while maintaining the same semantics (semantics-preserving code transformations). However, there has been a lack of in-depth analysis on how robust artificial intelligence models are against these types of transformations. This study systematically analyzes the impact of eight transformation techniques on the performance of six representative AI-based binary similarity detection models. It also introduces how models can lead to incorrect judgments, such as false positives and false negatives. For this, a dataset consisting of 9,565 transformed binaries from 620 original binaries was built for experimentation. The results show that the robustness to transformations varies based on the architecture and preprocessing methods of the models, and that even slight transformations can significantly degrade model performance, especially if the attacker designs the transformation precisely. This research emphasizes that, when designing AI models for supporting reverse engineering, model robustness against binary transformations should be considered as crucial as performance metrics. Abstract: Binary code analysis plays an essential role in cybersecurity, facilitating reverse engineering to reveal the inner workings of programs in the absence of source code. Traditional approaches, such as static and dynamic analysis, extract valuable insights from stripped binaries, but often demand substantial expertise and manual effort. Recent advances in deep learning have opened promising opportunities to enhance binary analysis by capturing latent features and disclosing underlying code semantics. Despite the growing number of binary analysis models based on machine learning, their robustness to adversarial code transformations at the binary level remains underexplored to date. In this work, we evaluate the robustness of deep learning models for the task of binary code similarity detection (BCSD) under semantics-preserving transformations. The unique nature of machine instructions presents distinct challenges compared to the typical input perturbations found in other domains. To achieve our goal, we introduce asmFooler, a system that evaluates the resilience of BCSD models using a diverse set of adversarial code transformations that preserve functional semantics. We construct a dataset of 9,565 binary variants from 620 baseline samples by applying eight semantics-preserving transformations across six representative BCSD models. Our major findings highlight several key insights: i) model robustness highly relies on the design of the processing pipeline, including code pre-processing, model architecture, and internal feature selection, which collectively determine how code semantics are captured; ii) the effectiveness of adversarial transformations is bounded by a transformation budget, shaped by model-specific constraints such as input size limits and the expressive capacity of semantically equivalent instructions; iii) well-crafted adversarial transformations can be highly effective, even when introducing minimal perturbations; and iv) such transformations efficiently disrupt the model's decision (e.g., misleading to false positives or false negatives) by focusing on semantically significant instructions. | Professor Hyungjoon Koo | kevin.koo@skku.edu, kevinkoo001.github.io | SecAI Lab | secai.skku.edu
- 작성일 2026-01-12
- 조회수 450
[Dec 30, 2025] SKKU Produces Winners of the 2025 Korea Talent Award (Sangho Kim, School of Convergence)

SKKU Produces Winners of the 2025 Korea Talent Award (Sangho Kim, School of Convergence) SKKU Has Four Students Selected as Winners of the 2025 Korea Talent Award in the University and Youth Categories (From left to right) Sangho Kim, Seungmin Kim, Jinhyung Lee, Yoonseo Heo A total of four students from our university have been selected as winners of the '2025 Korea Talent Award' in the University and Youth General Category, proving the university’s success in nurturing talents who excel in both academic achievements and social contributions. The '2025 Korea Talent Award,' organized by the Ministry of Education and managed by the Korea Scholarship Foundation, selected a total of 100 recipients, including 40 high school students and 60 university students and adults, after going through regional and central evaluations. This award was established to discover and foster future talents who can create new values based on creativity and passion, and contribute to the development of the community. ▲(From left to right) Awardees Seungmin Kim and Jinhyung Lee The selected students from Sungkyunkwan University are making meaningful achievements based on expertise and public service in their respective fields of study and activities. Sangho Kim, from the School of Convergence, has contributed to solving social issues through research and practical activities bridging academic and public sectors. Seungmin Kim, from the Department of Pharmacy, has continued his public contribution activities by connecting academic achievements based on his major with societal returns. Jinhyung Lee, from the Department of Mechanical Engineering, has accumulated significant research achievements by linking research with practical applications. Yoonseo Heo, from the Department of Sports Science, is showing great potential as a future talent in her field by balancing academic and professional activities. ▲(From left to right) Awardee Yoonseo Heo and Sangho Kim's certificate This award is seen as a demonstration of our university's ongoing success in nurturing well-rounded talents who possess both academic competence and social responsibility, in line with our educational philosophy of 'Self-Cultivation and Governance of Others (修己治人).' Moving forward, our university plans to continue fostering holistic talents who will lead the future of the nation and society by linking education, research, and social contributions. ▲ 2025 Korea Talent Award group photo
- 작성일 2026-01-05
- 조회수 373
[Dec 29, 2025] Professor Jaehoon Paul Jeong receives Minister of Science and ICT Award for leading international Inte...

Recipient of the Minister of Science and ICT Award for Leading International Internet Standardization Professor Jaehoon Paul Jeong of the Department of Computer Science and Engineering, College of Computing and Informatics, received the Minister of Science and ICT Award at the Global ICT Standards Conference (GISC) 2025 (https://gisc.or.kr/) held at EL Tower in Seoul on November 3. Since its launch in 2017, GISC has been the largest international event in Korea focused on standards and patents, bringing together experts to discuss the future of next-generation ICT technologies and standards. GISC 2025, held under the theme “AI for All,” gathered ICT standardization professionals, industry representatives, academics, and research institutions from around the world to share the latest knowledge and insights. The conference focused on standardization issues in key and emerging technologies such as AI, 6G, quantum technologies, and digital transformation, with global companies, international standardization organizations, and policy agencies participating to discuss interoperability, reliability, and the integration of standards and intellectual property, presenting a vision for the future digital society. Each year, GISC recognizes researchers who have made significant contributions to the development and standardization of international technologies by awarding the Minister of Science and ICT Award. Professor Jaehoon Paul Jeong was recognized at GISC 2025 for his contributions in developing cloud-based security service technologies and vehicle networking technologies for autonomous vehicles. These technologies were implemented in multiple international standards approved by the Internet Engineering Task Force (IETF), and further shared through open-source projects to demonstrate proof of concept (POC), earning him the Minister of Science and ICT Award for his contributions to ICT standardization in 2025. Figure 1. Receiving the Minister of Science and ICT Award for ICT Standard Figure 2. Certificate of the Minister of Science and ICT Award for ICT Standard Professor Jaehoon Paul Jeong has been engaged in Internet technology standardization at the Internet Engineering Task Force (IETF) for 23 years, from 2002 to 2025, and continues to actively participate as an ICT international standardization expert at TTA (Telecommunications Technology Association of Korea). As shown in Figure 3, Professor Paul co-authored RFC 8192 on problem statements and use cases for the I2NSF (Interface to Network Security Functions) Working Group (WG) for cloud-based security systems. He also served as editor for six I2NSF WG documents that have been approved as RFCs. These six documents are scheduled to be published as RFCs in the first half of 2026. The SKKU IoT Lab team led by Professor Paul (http://iotlab.skku.edu/) participated in IETF hackathons with the I2NSF Framework Project, winning four awards (IETF-97, IETF-99, IETF-100, IETF-103), contributing to global recognition of Korea's Internet technologies in the I2NSF field. Professor Paul also edited the problem statements and use case documents for the IPWAVE (IP Wireless Access in Vehicular Environments) WG for IPv6-based vehicular networking, which were published as RFC 9365. To implement proof of concept (POC) for I2NSF WG and IPWAVE WG standard documents, he leads open-source projects on GitHub. Over the past 23 years (2002–2025), he has served as lead author of two RFCs, RFC 4339 and RFC 5006 (later updated as RFC 6106 and RFC 8106). He actively participates in standardization at the IETF NMRG (Network Management Research Group) as editor for intent-based networking use case documents. Through these activities, Professor Paul has made significant contributions to the development of Internet technologies worldwide as an Internet expert. Figure 3. Cloud Security System Based on the I2NSF Framework Professor Paul’s SKKU team contributed to global recognition of Korea and Sungkyunkwan University as a leading institution in Internet technology development and standardization through their IETF standardization activities on the I2NSF cloud security system and IPWAVE vehicular networking. The following shows the Internet standard documents contributed by Professor Paul in the I2NSF and IPWAVE Working Groups. I2NSF Working Group: https://datatracker.ietf.org/wg/i2nsf/documents/ IPWAVE Working Group: https://datatracker.ietf.org/wg/ipwave/documents/ Professor Paul’s research team established the I2ICF (Interface to In-Network Computing Functions) group (https://mailman3.ietf.org/mailman3/lists/i2icf.ietf.org/) at the IETF to develop standard documents for controlling and managing mobile objects connected to 5G mobile networks (e.g., software-defined vehicles, robotic cars, robots, drones). At the IETF 124 Hackathon held in Montreal, Canada in November 2025, the team demonstrated I2ICF technology as a proof of concept (POC) and is working to establish a new working group within the IETF. Figure 4 shows Professor Paul’s hackathon team, and Figure 5 shows a poster presenting the implementation and test setup of the I2ICF hackathon project. This standardization work is part of Professor Paul’s standardization tasks under the IITP project “Development of SDV Software Framework Standards for Intelligent Converged Services.” Figure 4. I2ICF Hackathon Team at IETF 124 Meeting Figure 5. I2ICF Hackathon Project Poster at IETF 124 The following shows the I2ICF drafts currently being standardized by Professor Paul’s research team. I2ICF Problem Statement: https://datatracker.ietf.org/doc/draft-jeong-opsawg-i2icf-problem-statement/ I2ICF Framework: https://datatracker.ietf.org/doc/draft-jeong-opsawg-i2icf-framework/ Professor Paul’s research team develops networking and security technologies for the Internet and actively participates in Internet standardization at the IETF as Korea’s leading standardization expert. Their research results are also published annually in top academic journals. In addition, Professor Paul serves as the publicity chair for NetSoft 2025 and program committee chair for ICMU 2025, contributing to the global recognition of Korea and Sungkyunkwan University. He currently serves as the director of the Graduate School of Convergence Security at Sungkyunkwan University, responsible for nurturing talents in convergence security.
- 작성일 2026-01-08
- 조회수 447
[Dec 23, 2025] 2025 SKKU Rising-Fellowship: Professor Muhammad Khan of the School of Convergence Selected

2025 SKKU Rising-Fellowship Global Fellowship: Professor Muhammad Khan of the School of Convergence Selected 17 Professors Selected for the 2025 SKKU Rising-Fellowship This year, our university selected 17 professors as recipients of the newly established “2025 SKKU Rising-Fellowship.” The awardees are Professor Eunjin Shin (College of Social Sciences), Professor Seyoung Lee (College of Social Sciences), Professor Eunryung Lee (College of Economics), Professor Sangseok Yoo (College of Business), Professor Muhammad Khan (College of Computing and Informatics), Professor Hwaseon Lim (College of Natural Sciences), Professor Sejin Oh (College of Natural Sciences), Professor Jonghwan Ko (College of Information and Communication Engineering), Professor Sangmin Won (College of Information and Communication Engineering), Professor Jeonggyu Kim (College of Engineering), Professor Seokjun Kwon (College of Engineering), Professor Sungmin Yoon (College of Engineering), Professor Seungwon Lee (College of Medicine), Professor Mikyung Shin (Sungkyun Institute for Convergence), Professor Inki Kim (Sungkyun Institute for Convergence), Professor Wanki Bae (Institute of Nanoscience and Technology), and Professor Danbi Kang (Samsung Advanced Institute for Health Sciences and Technology). The SKKU Rising-Fellowship is an honorary title and special research support program awarded to outstanding early- to mid-career tenure-track faculty members who have either already established themselves at the highest national level or at a global standard in their academic fields, or who have demonstrated exceptional research achievements with strong potential to grow into world-class researchers. Recipients of the 2025 SKKU Rising-Fellowship were selected through a rigorous review process conducted by the selection committee, comprehensively considering the academic and qualitative excellence of research outcomes as well as global research impact. The award ceremony was held on Tuesday, December 23, with President Yoo Jibeom, representatives of the university foundation, and senior university administrators in attendance to congratulate and encourage the awardees. On behalf of the recipients, Professor Seyoung Lee of the College of Social Sciences and Professor Seokjun Kwon of the College of Engineering shared their acceptance remarks. President Yoo Jibeom stated that the university will continue to honor outstanding early- to mid-career researchers and actively support the creation of a culture and ecosystem that enable sustained challenge and growth.
- 작성일 2026-01-05
- 조회수 378
[Dec 16, 2025] PhD student Nivedita Singh(seclab, Advisor: Hyoungshick Kim), receives KIPS Undang Student Paper Award

Nivedita Singh, a PhD student at seclab (advised by Professor Hyoungshick Kim, https://seclab.skku.edu), received the Undang Student Paper Award from the Korea Information Processing Society (KIPS) for her paper, "Behind the Screen: How Cookies Become Your Identity’s Price Tag." The study analyzed cookie and tracking behaviors across 360 e-commerce websites in 18 countries, empirically demonstrating that privacy regulations such as GDPR and CCPA are often not properly enforced. The research revealed widespread security issues, including pre-consent user tracking, cookie lifetime violations, and serious vulnerabilities like XSS and CSRF, highlighting the urgent need for improved regulatory enforcement and better cookie management practices.
- 작성일 2026-01-08
- 조회수 436
[Dec 15, 2025] Prof. Hyungjoon Koo SecAI Lab & Prof. Sungjae Hwang SoftSec Lab, a paper accepted for NDSS '26

Eom Jiyong, a PhD student in SecAI Lab (Advisor: Professor Hyungjoon Koo, https://secai.skku.edu/) and Omar Abusabha, a PhD student in SoftSec Lab (Advisor: Professor Sungjae Hwang, https://softsec.skku.edu/), have co-authored a paper titled "A Deep Dive into Function Inlining and its Security Implications for ML-based Binary Analysis", which has been accepted for the premier security conference, The Network and Distributed System Security Symposium 2026 (NDSS '26), and is scheduled to be presented in February 2026. Function inlining optimization is a representative technique used by compilers to improve program performance. Instead of making a function call, the compiler directly inserts the function's code at the call site, reducing the overhead associated with the function call. Function inlining is applied extensively throughout the compilation process, and some inlining occurs even when optimization options are disabled (-O0). Recently, machine learning models that assist in binary reverse engineering rely heavily on various static features of functions. However, in-depth analyses of how normal inlining optimizations affect the performance of these models have not yet been sufficiently conducted. The study shows that function inlining can significantly distort the static features used by ML models, leading to performance degradation, and that attackers can intentionally exploit this using only the compiler's default flags, without employing complex techniques such as obfuscation. To investigate this, the authors first analyzed the inlining optimization mechanisms of the LLVM compiler toolchain and systematically organized the compiler options affecting inlining. They then derived combinations of options that induce higher inlining than typical optimization levels. Subsequently, experiments were conducted across five ML-based tasks—including binary reverse engineering and malware detection—using a total of 20 ML models. Abstract: A function inlining optimization is a widely used transformation in modern compilers, which replaces a call site with the callee's body in need. While this transformation improves performance, it significantly impacts static features such as machine instructions and control flow graphs, which are crucial to binary analysis. Yet, despite its broad impact, the security impact of function inlining remains underexplored to date. In this paper, we present the first comprehensive study of function inlining through the lens of machine learning-based binary analysis. To this end, we dissect the inlining decision pipeline within the LLVM's cost model and explore the combinations of the compiler options that aggressively promote the function inlining ratio beyond standard optimization levels, which we term extreme inlining. We focus on five ML-assisted binary analysis tasks for security, using 20 unique models to systematically evaluate their robustness under extreme inlining scenarios. Our extensive experiments reveal several significant findings: i) function inlining, though a benign transformation in intent, can (in)directly affect ML model behaviors, being potentially exploited by evading discriminative or generative ML models; ii) ML models relying on static features can be highly sensitive to inlining; iii) subtle compiler settings can be leveraged to deliberately craft evasive binary variants; and iv) inlining ratios vary substantially across applications and build configurations, undermining assumptions of consistency in training and evaluation of ML models. | Professor Hyungjoon Koo | kevin.koo@skku.edu, kevinkoo001.github.io | SecAI Lab | secai.skku.edu/ | Professor Sungjae Hwang | sungjaeh@skku.edu | SoftSec Lab | softsec.skku.edu/
- 작성일 2026-01-08
- 조회수 503
[Dec 02, 2025] SW Convergence College, Department of Real-World Media Engineering Annual Research Review Completed

The Department of Immersive Media Engineering in the College of Software Convergence Successfully Concludes its Annual Research Review The Department of Immersive Media Engineering in the College of Software Convergence (Department Head: Professor Eun-seok Ryu) successfully held its 2025 Annual Research Review event on Thursday, November 27th at 4:30 PM in the Global R&E Lounge on the 5th floor of the International Building on the Humanities and Social Sciences Campus. This event, co-hosted by four departments—the Department of Immersive Media Engineering, the Department of Artificial Intelligence Convergence, the Department of Interaction Science, and the Department of Artificial Intelligence Convergence—featured 41 research presentations across six areas: XR/VR & Immersive Experiences, 3D Gaussian Splatting & Graphics Systems, Multimodal Understanding & Generation, Human-AI Interaction & Social Computing, AI for Emotion & Mental Health, and Data-Driven Modeling & Recommendation. The event provided a meaningful forum for examining the present and future of Immersive Media research. The presentations were presented in the form of poster exhibitions and demonstrations, and a lively discussion ensued on the practical applicability and technological scalability of the research. Preceding the event, the Industrial Advisory Board (IAB) pre-meeting was attended by representatives from major ICT and content companies and research institutes, including LG Electronics, Samsung Electronics, Sanghwa, Olympla, SOS Lab, the Electronics and Telecommunications Research Institute (ETRI), LG U+, LG HelloVision, and the Institute of Information and Communications Technology Planning and Evaluation (IITP). The participating experts exchanged in-depth views on key technology trends demanded by the industry, including XR devices, robot-based vision technology, LiDAR sensors and volumetric imaging, AI-based immersive media services, future networks, and Web3 technologies, as well as the direction of industry-academia-research cooperation. They emphasized the importance of building a collaborative research ecosystem between industry and academia. Following a presentation of research results and expert evaluations, the "Outstanding Research Award" ceremony was held, with winners selected for both the undergraduate and graduate categories. In the undergraduate category, Kang Min-gu, a student majoring in Artificial Intelligence Convergence, received the Best Research Award, while Kim Soo-hyun and Oh Kyung-jun received the Excellence in Research Award. In the graduate category, Researcher Lee Yu-bin of the Department of Artificial Intelligence Convergence received the Best Research Award. The Outstanding Research Awards went to Researcher Kim Jong-han of the Department of Realistic Media Engineering, Researcher Oh Min-woo of the Department of Metabiohealth and Researcher Park Min-soo (and his team) of the Department of Artificial Intelligence Convergence, Researcher Joo Min-jun of the Department of Realistic Media Engineering, and Researcher Jeong Ui-jun of the Department of Realistic Media Engineering. This award ceremony recognized the efforts of researchers who demonstrated creative research capabilities and the potential for practical technological advancement. Furthermore, Alumni Association Advisor Ryu Deok-hee (Honorary Chairman of Kyungdong Pharmaceutical) attended the event, offering practical advice and heartfelt encouragement to students growing into researchers who will lead future technologies. Students and researchers gained valuable insights into the practical capabilities and research attitudes required in industry, providing valuable insights into the research process. Dean Eunseok Ryu of the Department of Immersive Media Engineering, who planned the event, stated, "The Annual Research Review is a crucial forum for researchers to share their achievements and discover new collaboration opportunities. We will continue to grow as a leading global research hub in the field of Immersive Media Engineering." With support from the Ministry of Science and ICT's Virtual Convergence Graduate School project, the Department of Immersive Media Engineering operates an overseas research program and selects outstanding graduate students. It also continuously expands its research environment and international collaboration system to cultivate future talent in image processing, graphics, and artificial intelligence. This Annual Research Review concluded as a meaningful event that not only shared the achievements of undergraduate and graduate researchers, but also strengthened collaboration with industry and laid the foundation for future growth.
- 작성일 2025-12-09
- 조회수 664

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