相关论文: Anonymizing Test Data in Android: Does It Hurt?
Android applications collecting data from users must protect it according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation…
The privacy of personal information has received significant attention in mobile software. Although previous researchers have designed some methods to identify the conflict between app behavior and privacy policies, little is known about…
A growing concern with advertisement libraries on Android is their ability to exfiltrate personal information from their host applications. While previous work has looked at the libraries' abilities to measure private information on their…
Security of mobile apps affects the security of their users. This has fueled the development of techniques to automatically detect vulnerabilities in mobile apps and help developers secure their apps; specifically, in the context of Android…
Dating apps for mobile devices, one popular GeoSocial app category, are growing increasingly popular. These apps encourage the sharing of more personal information than conventional social media apps, including continuous location data.…
Process mining enables organizations to discover and analyze their actual processes using event data. Event data can be extracted from any information system supporting operational processes, e.g., SAP. Whereas the data inside such systems…
Pervasive use of software applications continues to challenge user privacy when users interact with software systems. Even though privacy practices such as Privacy by Design (PbD), have clear in- structions for software developers to embed…
When machine learning is used for Android malware detection, an app needs to be represented in a numerical format for training and testing. We identify a widespread occurrence of distinct Android apps that have identical or nearly identical…
Despite extensive security research on various Android components, such as kernel or runtime, little attention has been paid to the proprietary vendor blobs within Android firmware. In this paper, we conduct a large-scale empirical study to…
With mobile applications and associated services becoming increasingly popular, concerns are being raised about private data leakages have raised. Previous solutions to this well-known set of problems have approached it from the ground up…
Android apps are event-driven, and their execution is often interrupted by external events. This interruption can cause data loss issues that annoy users. For instance, when the screen is rotated, the current app page will be destroyed and…
Android apps must work correctly even if their execution is interrupted by external events. For instance, an app must work properly even if a phone call is received, or after its layout is redrawn because the smartphone has been rotated.…
Foundation models trained on large-scale de-identified electronic health records (EHRs) hold promise for clinical applications. However, their capacity to memorize patient information raises important privacy concerns. In this work, we…
In this paper, we propose a model that could be used by system developers to measure the privacy risk perceived by users when they disclose data into software systems. We first derive a model to measure the perceived privacy risk based on…
Social graphs derived from online social interactions contain a wealth of information that is nowadays extensively used by both industry and academia. However, as social graphs contain sensitive information, they need to be properly…
Voice anonymisation aims to conceal the voice identity of speakers in speech recordings. Privacy protection is usually estimated from the difficulty of using a speaker verification system to re-identify the speaker post-anonymisation.…
We present an analysis of 12 million instances of privacy-relevant reviews publicly visible on the Google Play Store that span a 10 year period. By leveraging state of the art NLP techniques, we examine what users have been writing about…
Accurate detection of third-party libraries (TPLs) is fundamental to Android security, supporting vulnerability tracking, malware detection, and supply chain auditing. Despite many proposed tools, their real-world effectiveness remains…
Auditing differential privacy has emerged as an important area of research that supports the design of privacy-preserving mechanisms. Privacy audits help to obtain empirical estimates of the privacy parameter, to expose flawed…
With the requirements and emphases on privacy transparency placed by regulations such as GDPR and CCPA, the Google Play Store requires Android developers to more responsibly communicate their apps' privacy practices to potential users by…