Demo Data from EDBT 2026 / reviewers in the wild / expert
Stefan Triller
dblp:53/7871
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Security and privacy · 1Software engineering, systems software and programming languages · 1
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
2 papers |
Systems and software security · 73% Malware analysis · 27% | |
| Software engineering, system software, and programming languages
1 paper |
Software testing · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Malware analysis
android malware |
0.3 | 1 | 2017 | Making malory behave maliciously: targeted fuzzing of android execution environments · ICSE 2017 |
Systems and software security
exploitation |
0.2 | 1 | 2016 | An In-Depth Study of More Than Ten Years of Java Exploitation · CCS 2016 |
Systems and software security
vulnerability discovery |
0.2 | 1 | 2016 | An In-Depth Study of More Than Ten Years of Java Exploitation · CCS 2016 |
Software testing
fuzzing |
0.1 | 1 | 2017 | Making malory behave maliciously: targeted fuzzing of android execution environments · ICSE 2017 |
Methods — techniques the papers use, named apart from their topics
static analysis · 0.6search-based algorithm · 0.6dynamic analysis · 0.6empirical study · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Making malory behave maliciously: targeted fuzzing of android execution environmentsabstractAndroid applications, or apps, provide useful features to end-users, but many apps also contain malicious behavior. Modern malware makes understanding such behavior challenging by behaving maliciously only under particular conditions. For example, a malware app may check whether it runs on a real device and not an emulator, in a particular country, and alongside a specific target app, such as a vulnerable banking app. To observe the malicious behavior, a security analyst must find out and emulate all these app-specific constraints. This paper presents FuzzDroid, a framework for automatically generating an Android execution environment where an app exposes its malicious behavior. The key idea is to combine an extensible set of static and dynamic analyses through a search-based algorithm that steers the app toward a configurable target location. On recent malware, the approach reaches the target location in 75% of the apps. In total, we reach 240 code locations within an average time of only one minute. To reach these code locations, FuzzDroid generates 106 different environments, too many for a human analyst to create manually. Siegfried Rasthofer, Steven Arzt, Stefan Triller, Michael Pradel |
ICSE | 3 |
| 2016 | An In-Depth Study of More Than Ten Years of Java ExploitationabstractWhen created, the Java platform was among the first runtimes designed with security in mind. Yet, numerous Java versions were shown to contain far-reaching vulnerabilities, permitting denial-of-service attacks or even worse allowing intruders to bypass the runtime's sandbox mechanisms, opening the host system up to many kinds of further attacks. Philipp Holzinger, Stefan Triller, Alexandre Bartel, Eric Bodden |
CCS | 2 |
| 2010 | Towards a Comprehensive Teamwork Model for Highly Dynamic Domains
Hendrik Skubch, Michael Wagner 0001, Roland Reichle, Stefan Triller, Kurt Geihs |
ICAART (2) | 4 |