VLDB 2026 Research / reviewers in the wild / expert
Noah Mauthe
dblp:292/7992
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2023
0009-0006-9443-6455ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021Security and privacy · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Characterizing the Use of Code Obfuscation in Malicious and Benign Android AppsabstractObfuscation is frequently used by both benign and malicious Android apps. Since static analysis of obfuscated apps often produces incomplete or misleading results, the problems of identifying and quantifying the use of specific obfuscation techniques in apps has received significant attention. Even though several existing works have addressed these problems, most studies focus on data obfuscation methods such as identifier renaming and string obfuscation, while more advanced code obfuscation methods, such as reflection and control-flow obfuscation, have received less attention. Moreover, existing approaches to detecting Android code obfuscation have significant limitations, as shown by a detailed survey that we present as part of this paper. This is in part due to a fundamental “bootstrapping” problem: since, on one hand, the landscape of Android code obfuscation is poorly known, researchers have very little guidance when designing new detection methods. On the other hand, the lack of detection methods mean that the obfuscation landscape is bound to remain largely unexplored. Ulf Kargén, Noah Mauthe, Nahid Shahmehri |
ARES | 2 |
| 2023 | Android decompiler performance on benign and malicious apps: an empirical studyabstractAbstract Decompilers are indispensable tools in Android malware analysis and app security auditing. Numerous academic works also employ an Android decompiler as the first step in a program analysis pipeline. In such settings, decompilation is frequently regarded as a “solved” problem, in that it is simply expected that source code can be accurately recovered from an app. On the other hand, it is known that, e.g, obfuscation can negatively impact a decompiler’s effectiveness. Therefore, in order to better understand potential failure modes of, e.g., automated analysis pipelines involving decompilation, it is important to characterize the performance of decompilers on both benign and malicious apps. To this end, we have performed what is, to the best of our knowledge, the first large-scale study of Android decompilation failure rates, using three sets of apps; namely, 3,018 open-source apps, 13,601 apps crawled from Google Play, and an existing collection of 24,553 malware samples. In addition to the state-of-the-art Dalvik bytecode decompiler Jadx, we also studied the performance of three popular Java decompilers. Furthermore, this paper also presents the findings from a follow-up study on 54,945 malware apps, where we additionally performed an analysis of the reasons for decompilation failures. Our study revealed that decompilers generally have very low failure rates, and that few failures on benign apps appear to be related to obfuscation. On malware, however, obfuscation appears to be a more prominent cause of failures, although the vast majority of malicious apps could still be fully decompiled by an ensemble of decompilers. Ulf Kargén, Noah Mauthe, Nahid Shahmehri |
Empir. Softw. Eng. | 2 |
| 2021 | A Large-Scale Empirical Study of Android App DecompilationabstractDecompilers are indispensable tools in Android malware analysis and app security auditing. Numerous academic works also employ an Android decompiler as the first step in a program analysis pipeline. In such settings, decompilation is frequently regarded as a "solved" problem, in that it is simply expected that source code can be accurately recovered from an app. While a large proportion of methods in an app can typically be decompiled successfully, it is common that at least some methods fail to decompile. In order to better understand the practical applicability of techniques in which decompilation is used as part of an automated analysis, it is important to know the actual expected failure rate of Android decompilation. To this end, we have performed what is, to the best of our knowledge, the first large-scale study of Android decompilation failure rates. We have used three sets of apps, consisting of, respectively, 3,018 open-source apps, 13,601 apps from a recent crawl of Google Play, and a collection of 24,553 malware samples. In addition to the state-of-the-art Dalvik bytecode decompiler jadx, we used three popular Java decompilers. While jadx achieves an impressively low failure rate of only 0.02% failed methods per app on average, we found that it manages to recover source code for all methods in only 21% of the Google Play apps.We have also sought to better understand the degree to which in-the-wild obfuscation techniques can prevent decompilation. Our empirical evaluation, complemented with an indepth manual analysis of a number of apps, indicate that code obfuscation is quite rarely encountered, even in malicious apps. Moreover, decompilation failures mostly appear to be caused by technical limitations in decompilers, rather than by deliberate attempts to thwart source-code recovery by obfuscation. This is an encouraging finding, as it indicates that near-perfect Android decompilation is, at least in theory, achievable, with implementation-level improvements to decompilation tools. Noah Mauthe, Ulf Kargén, Nahid Shahmehri |
SANER | 1 |