EDBT 2026 Demo / reviewers in the wild / expert
Yoonjong Na
dblp:273/7426
· DBLP profile ↗
3ranked-venue papers
2as first author
2since 2021 · last 2024
0000-0002-4071-0547ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Software maintenance and evolution · 77% Program analysis · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution
software dependencies |
0.8 | 1 | 2024 | CNEPS: A Precise Approach for Examining Dependencies among Third-Party C/C++ Open-Source Components · ICSE 2024 |
Program analysis
static analysis |
0.2 | 1 | 2024 | CNEPS: A Precise Approach for Examining Dependencies among Third-Party C/C++ Open-Source Components · ICSE 2024 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | CNEPS: A Precise Approach for Examining Dependencies among Third-Party C/C++ Open-Source ComponentsabstractThe rise in open-source software (OSS) reuse has led to intricate dependencies among third-party components, increasing the demand for precise dependency analysis. However, owing to the presence of reused files that are difficult to identify the originating components (i.e., indistinguishable files) and duplicated components, precisely identifying component dependencies is becoming challenging. Yoonjong Na, Seunghoon Woo, Joomyeong Lee, Heejo Lee |
ICSE | 1 |
| 2021 | QuickBCC: Quick and Scalable Binary Vulnerable Code Clone Detection
Hajin Jang, Kyeongseok Yang, Geonwoo Lee, Yoonjong Na, Jeremy D. Seideman, Shoufu Luo, Heejo Lee, Sven Dietrich |
SEC | 4 |
| 2020 | Enhancing the Reliability of IoT Data Marketplaces through Security Validation of IoT DevicesabstractIoT data marketplaces are being developed to help cities and communities create large scale IoT applications. Such data marketplaces let the IoT device owners sell their data to the application developers. Following this application development model, the application developers need not deploy their own IoT devices when developing IoT applications; instead, they can buy data from a data marketplace. In a marketplace-based IoT application, the application developers are making critical business and operation decisions using the data produced by seller's IoT devices. Under these circumstances, it is crucial to verify and validate the security of IoT devices.In this paper, we assess the security of IoT data marketplaces. In particular, we discuss what kind of vulnerabilities exist in IoT data marketplaces using the well-known STRIDE model, and present a security assessment and certification framework for IoT data marketplaces to help the device owners to examine the security vulnerabilities of their devices. Most importantly, our solution certifies the IoT devices when they connect to the data marketplace, which helps the application developers to make an informed decision when buying and consuming data from a data marketplace. To demonstrate the effectiveness of the proposed approach, we have developed a proof-of-concept using I3 (Intelligent IoT Integrator), which is an open-source IoT data marketplace developed at the University of Southern California, and IoTcube, which is a vulnerability detection toolkit developed by researchers at Korea University. Through this work, we show that it is possible to increase the reliability of a IoT data marketplace while not damaging the convenience of the users. Yoonjong Na, Yejin Joo, Heejo Lee, Xiangchen Zhao, Kurian Karyakulam Sajan, Gowri Sankar Ramachandran, Bhaskar Krishnamachari |
DCOSS | 1 |