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Many Android applications collect data from users. When they do, they must protect this collected data according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the…
Android is the most widely deployed end-user focused operating system. With its growing set of use cases encompassing communication, navigation, media consumption, entertainment, finance, health, and access to sensors, actuators, cameras,…
Enterprise environment often screens large-scale (millions of lines of code) codebases with static analysis tools to find bugs and vulnerabilities. Parfait is a static code analysis tool used in Oracle to find security vulnerabilities in…
Android's graphical password unlock remains one of the most widely used schemes for phone unlock authentication, and it is has been studied extensively in the last decade since its launch. We have learned that users' choice of patterns…
Clustering has been well studied for desktop malware analysis as an effective triage method. Conventional similarity-based clustering techniques, however, cannot be immediately applied to Android malware analysis due to the excessive use of…
Internet of Things (IoT) devices are becoming increasingly important. These devices are often resource-limited, hindering rigorous enforcement of security policies. Assessing the vulnerability of IoT devices is an important problem, but…
We introduce the Android Security Framework (ASF), a generic, extensible security framework for Android that enables the development and integration of a wide spectrum of security models in form of code-based security modules. The design of…
In the digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking, and others offer support for two-factor authentication.…
Cryptojacking is the permissionless use of a target device to covertly mine cryptocurrencies. With cryptojacking, attackers use malicious JavaScript codes to force web browsers into solving proof-of-work puzzles, thus making money by…
The growth in the number of Android and Internet of Things (IoT) devices has witnessed a parallel increase in the number of malicious software (malware), calling for new analysis approaches. We represent binaries using their graph…
In this paper, we propose to identify compromised mobile devices from a network administrator's point of view. Intuitively, inadvertent users (and thus their devices) who download apps through untrustworthy markets are often allured to…
The pervasiveness of the Android operating system, with the availability of applications almost for everything, is readily accessible in the official Google play store or a dozen alternative third-party markets. Additionally, the vital role…
The malware analysis and detection research community relies on the online platform VirusTotal to label Android apps based on the scan results of around 60 antiviral scanners. Unfortunately, there are no standards on how to best interpret…
Android OS is severely fragmented by API updates and device vendors' OS customization, creating a market condition where vastly different OS versions coexist. This gives rise to compatibility crash problems where Android apps crash on…
Widely-used Android static program analysis tools, e.g., Amandroid and FlowDroid, perform the whole-app inter-procedural analysis that is comprehensive but fundamentally difficult to handle modern (large) apps. The average app size has…
The packaging model of Android apps requires the entire code necessary for the execution of an app to be shipped into one single apk file. Thus, an analysis of Android apps often visits code which is not part of the functionality delivered…
Contact tracing has historically been used to retard the spread of infectious diseases, but if it is exercised by hand in large-scale, it is known to be a resource-intensive and quite deficient process. Nowadays, digital contact tracing has…
Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on features statically extracted from the application, such as…
Mobile applications, particularly those from social media platforms such as WeChat and TikTok, are evolving into "super apps" that offer a wide range of services such as instant messaging and media sharing, e-commerce, e-learning, and…
With the number of new mobile malware instances increasing by over 50\% annually since 2012 [24], malware embedding in mobile apps is arguably one of the most serious security issues mobile platforms are exposed to. While obfuscation…