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The reliability of machine learning critically depends on dataset quality. While machine learning applied to computer vision and natural language processing benefits from high-quality benchmark datasets, cyber security often falls behind,…
Mobile applications are being used every day by more than half of the world's population to perform a great variety of tasks. With the increasingly widespread usage of these applications, the need arises for efficient techniques to test…
Performance issues in Android applications significantly undermine users' experience, engagement, and retention, which is a long-lasting research topic in academia. Unlike functionality issues, performance issues are more difficult to…
The large demand of mobile devices creates significant concerns about the quality of mobile applications (apps). Developers need to guarantee the quality of mobile apps before it is released to the market. There have been many approaches…
With the rapid advancement of machine learning (ML), ML-based Android malware detection has gained significant popularity due to its ability to automatically learn malicious patterns from Android apps. However, the lack of an in-depth and…
The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering search results based on relational databases, they often neglect…
Analytics on personal data, such as individuals' mobility, financial, and health data can be of significant benefit to society. Such data is already collected by smartphones, apps and services today, but liberal societies have so far…
Android is undergoing unprecedented malicious threats daily, but the existing methods for malware detection often fail to cope with evolving camouflage in malware. To address this issue, we present HAWK, a new malware detection framework…
As the smartphone market leader, Android has been a prominent target for malware attacks. The number of malicious applications (apps) identified for it has increased continually over the past decade, creating an immense challenge for all…
People usually seek out varied information to deal with their health problems. However, the large volume of information available may present challenges for the public to distinguish good from suboptimal advice. How to ensure the right…
The Android operating system is the most spread mobile platform in the world. Therefor attackers are producing an incredible number of malware applications for Android. Our aim is to detect Android's malware in order to protect the user. To…
In the past few years, the use of smartphones has increased exponentially, and so have the capabilities of such devices. Together with an increase in raw processing power, modern smartphones are equipped with a wide variety of sensors and…
Driven by the popularity of the Android system, Android app markets enjoy a booming prosperity in recent years. One critical problem for modern Android app markets is how to prevent apps that are going to receive low ratings from reaching…
The Android middleware, in particular the so-called systemserver, is a crucial and central component to Android's security and robustness. To understand whether the systemserver provides the demanded security properties, it has to be…
Smartphone apps usually have access to sensitive user data such as contacts, geo-location, and account credentials and they might share such data to external entities through the Internet or with other apps. Confidentiality of user data…
We are in the dawn of deep learning explosion for smartphones. To bridge the gap between research and practice, we present the first empirical study on 16,500 the most popular Android apps, demystifying how smartphone apps exploit deep…
The rise of Virtual Reality (VR) has provided developers with an unprecedented platform for creating games and applications (apps) that require distinct inputs, different from those of conventional devices like smartphones. The Meta Quest…
Android's security model severely limits the capabilities of anti-malware software. Unlike commodity anti-malware solutions on desktop systems, their Android counterparts run as sandboxed applications without root privileges and are limited…
We present Anadroid, a static malware analysis framework for Android apps. Anadroid exploits two techniques to soundly raise precision: (1) it uses a pushdown system to precisely model dynamically dispatched interprocedural and…
The Android OS has become the most popular mobile operating system leading to a significant increase in the spread of Android malware. Consequently, several static and dynamic analysis systems have been developed to detect Android malware.…