Demo Data from EDBT 2026 / reviewers in the wild / expert
Tian Yang Ooi
dblp:386/2192
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0000-9527-6277ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 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.
| Network and information security
1 paper |
Systems and software security · 50% Privacy and data protection · 50% | |
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 50% Software maintenance and evolution · 50% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection › privacy management › user-controlled privacy › personal data management
user data protection |
0.8 | 1 | 2024 | Exploring ChatGPT App Ecosystem: Distribution, Deployment and Security · ASE 2024 |
Software maintenance and evolution › software ecosystems › software ecosystem analysis
app ecosystem analysis |
0.2 | 1 | 2024 | Exploring ChatGPT App Ecosystem: Distribution, Deployment and Security · ASE 2024 |
Empirical software engineering
mining software repositories |
0.2 | 1 | 2024 | Exploring ChatGPT App Ecosystem: Distribution, Deployment and Security · ASE 2024 |
Methods — techniques the papers use, named apart from their topics
empirical study · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Exploring ChatGPT App Ecosystem: Distribution, Deployment and SecurityabstractChatGPT has enabled third-party developers to create plugins to expand ChatGPT's capabilities. These plugins are distributed through OpenAI's plugin store, making them easily accessible to users. With ChatGPT as the backbone, this app ecosystem has illustrated great business potential by offering users personalized services in a conversational manner. Nonetheless, many crucial aspects regarding app development, deployment, and security of this ecosystem have yet to be thoroughly studied in the research community, potentially hindering a broader adoption by both developers and users. In this work, we conduct the first comprehensive study of the ChatGPT app ecosystem, aiming to illuminate its landscape for our research community. Our study examines the distribution and deployment models in the integration of LLMs and third-party apps, and assesses their security and privacy implications. We uncover an uneven distribution of functionality among ChatGPT plugins, highlighting prevalent and emerging topics. We also identify severe flaws in the authentication and user data protection for third-party app APIs integrated within LLMs, revealing a concerning status quo of security and privacy in this app ecosystem. Our work provides insights for the secure and sustainable development of this rapidly evolving ecosystem. Chuan Yan, Ruomai Ren, Mark Huasong Meng, Liuhuo Wan, Tian Yang Ooi, Guangdong Bai |
ASE | 5 |