Related papers: Unpacking Privacy Labels: A Measurement and Develo…
Differential privacy is a cryptographically-motivated definition of privacy which has gained significant attention over the past few years. Differentially private solutions enforce privacy by adding random noise to a function computed over…
Virtual Reality (VR) has gained increasing traction among various domains in recent years, with major companies such as Meta, Pico, and Microsoft launching their application stores to support third-party developers in releasing their…
While there have been various studies towards Android apps and their development, there is limited discussion of the broader class of apps that fall in the fake area. Fake apps and their development are distinct from official apps and…
We develop DroidCCT, a distributed test framework to evaluate the scale of a wide range of failures/bugs in cryptography for end users. DroidCCT relies on passive analysis of artifacts from the execution of cryptographic operations in the…
Secure communication is an integral feature of many Internet services. The widely deployed TLS protects reliable transport protocols. DTLS extends TLS security services to protocols relying on plain UDP packet transport, such as VoIP or IoT…
Synthetic data (SD) have garnered attention as a privacy enhancing technology. Unfortunately, there is no standard for quantifying their degree of privacy protection. In this paper, we discuss proposed quantification approaches. This…
The age of technology has created a huge market for smartphones and Apps usage and a new generation has been created based on knowledge sharing. Now knowledge has been made easily accessible by Apps but; are users even aware of the…
This article introduces a distributed model of trust for app developers in Android and iOS mobile ecosystems. The model aims to allow the co-existence of multiple app stores and distribution channels while retaining a high level of safety…
Collecting and analyzing massive data generated from smart devices have become increasingly pervasive in crowdsensing, which are the building blocks for data-driven decision-making. However, extensive statistics and analysis of such data…
Android is a widely deployed operating system that employs a permission-based access control model. The Android Permissions System (APS) is responsible for mediating resource requests from applications. APS is a critical component of the…
Recent years, local differential privacy (LDP) has been adopted by many web service providers like Google \cite{erlingsson2014rappor}, Apple \cite{apple2017privacy} and Microsoft \cite{bolin2017telemetry} to collect and analyse users' data…
While the public claim concern for their privacy, they frequently appear to overlook it. This disparity between concern and behaviour is known as the Privacy Paradox. Such issues are particularly prevalent on wearable devices. These…
Prior studies on mobile app analysis often analyze apps across different categories or focus on a small set of apps within a category. These studies either provide general insights for an entire app store which consists of millions of apps,…
The huge computation demand of deep learning models and limited computation resources on the edge devices calls for the cooperation between edge device and cloud service by splitting the deep models into two halves. However, transferring…
The analysis of the privacy properties of Privacy-Preserving Ads APIs is an area of research that has received strong interest from academics, industry, and regulators. Despite this interest, the empirical study of these methods is hindered…
As mobile applications (apps) become ubiquitous in everyday life, it is crucial for developers to prioritize accessibility for users with diverse abilities. While previous research has identified widespread accessibility issues and raised…
With low-cost computing devices, improved sensor technology, and the proliferation of data-driven algorithms, we have more data than we know what to do with. In transportation, we are seeing a surge in spatiotemporal data collection. At the…
The proliferation of mobile applications (apps) has made it crucial to ensure their accessibility for users with disabilities. However, there is a lack of research on the real-world challenges developers face in implementing mobile…
While extremely valuable to achieve advanced functions, mobile phone sensors can be abused by attackers to implement malicious activities in Android apps, as experimentally demonstrated by many state-of-the-art studies. There is hence a…
Using real-world study data usually requires contractual agreements where research results may only be published in anonymized form. Requiring formal privacy guarantees, such as differential privacy, could be helpful for data-driven…