VLDB 2026 Research / reviewers in the wild / expert
Runze Tan
dblp:385/7822
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0001-8854-5720ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 2 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 |
Web and mobile security · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and mobile security › mobile security
android application security |
0.9 | 1 | 2025 | ARAP: Demystifying Anti Runtime Analysis Code in Android Apps · IEEE Trans. Software Eng. 2025 |
Web and mobile security
mobile security |
0.9 | 1 | 2025 | ARAP: Demystifying Anti Runtime Analysis Code in Android Apps · IEEE Trans. Software Eng. 2025 |
Methods — techniques the papers use, named apart from their topics
static analysis · 1.7dynamic analysis · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Assessing the capability of android dynamic analysis tools to combat anti-runtime analysis techniques
Dewen Suo, Lei Xue 0001, Weihao Huang, Runze Tan, Guozi Sun |
J. Syst. Softw. | 4 |
| 2025 | ARAP: Demystifying Anti Runtime Analysis Code in Android AppsabstractWith the continuous growth in the usage of Android apps, ensuring their security has become critically important. An increasing number of malicious apps adopt anti-analysis techniques to evade security measures. Although some research has started to consider anti-runtime analysis (ARA), it is unfortunate that they have not systematically examined ARA techniques. Furthermore, the rapid evolution of ARA technology exacerbates the issue, leading to increasingly inaccurate analysis results. To effectively analyze Android apps, understanding their adopted ARA techniques is necessary. However, no systematic investigation has been conducted thus far.In this paper, we conduct the first systematic study of the ARA implementations in a wide range of 117,270 Android apps (including both malicious and benign ones) collected between 2016 and 2023. Additionally, we propose a specific investigation tool namedARAPto assist this study by leveraging both static and dynamic analysis. According to the evaluation results,ARAPnot only effectively identifies the ARA implementations in Android apps but also reveals many important findings. For instance, almost all apps have implemented at least one category of ARA technology (99.6% for benign apps and 97.0% for malicious apps). Dewen Suo, Lei Xue 0001, Le Yu 0002, Runze Tan, Weihao Huang, Guozi Sun |
IEEE Trans. Software Eng. | 4 |