Related papers: Is Downloading this App Consistent with my Values?…
We provide tools for sharing sensitive data when the data curator does not know in advance what questions an (untrusted) analyst might ask about the data. The analyst can specify a program that they want the curator to run on the dataset.…
Online Automated Privacy Policy Generators (APPGs) are tools used by app developers to quickly create app privacy policies which are required by privacy regulations to be incorporated to each mobile app. The creation of these tools brings…
User interface personalization enhances digital efficiency, usability, and accessibility. However, in user-driven setups, limited support for identifying and evaluating worthwhile opportunities often leads to underuse. We explore a…
Although the NLP community has adopted central differential privacy as a go-to framework for privacy-preserving model training or data sharing, the choice and interpretation of the key parameter, privacy budget $\varepsilon$ that governs…
The pursuit of improved accuracy in recommender systems has led to the incorporation of user context. Context-aware recommender systems typically handle large amounts of data which must be uploaded and stored on the cloud, putting the…
The growing popularity of mobile and wearable devices with built-in cameras, the bright prospect of camera related applications such as augmented reality and life-logging system, the increased ease of taking and sharing photos, and advances…
User profiling is crucial in providing personalised services, as it relies on analysing user behaviour and preferences to deliver targeted services. This approach enhances user experience and promotes heightened engagement. Nevertheless,…
Cloud platforms are increasingly being used to run HPC workloads. Major cloud providers offer a wide variety of virtual machine (VM) types, enabling users to find the optimal balance between performance and cost. However, this extensive…
Ensuring equitable privacy experiences remains a challenge, especially for marginalised and vulnerable populations (MVPs) who often hesitate to participate or use digital services due to concerns about the privacy of their sensitive…
Those concerned about privacy worry that personal data changes hands too easily. We argue that the actual challenge is the exact opposite: our data does not flow well enough, cultivating a reliance on questionable and often unlawful…
\begin{abstract} This paper comprehensively analyzes privacy policies in AR/VR applications, leveraging BERT, a state-of-the-art text classification model, to evaluate the clarity and thoroughness of these policies. By comparing the privacy…
Differential privacy ensures the security of individual privacy but poses challenges to data exploration processes because the limited privacy budget incapacitates the flexibility of exploration and the noisy feedback of data requests leads…
Location privacy has been extensively studied in the literature. However, existing location privacy models are either not rigorous or not customizable, which limits the trade-off between privacy and utility in many real-world applications.…
This paper addresses the question whether the recently proposed approach of concise privacy notices in apps and on websites is effective in raising user awareness. To assess the effectiveness in a realistic setting, we included concise…
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…
In the age of personal voice assistants, the question of privacy arises. These digital companions often lack memory of past interactions, while relying heavily on the internet for speech processing, raising privacy concerns. Modern…
Speech data carries a range of personal information, such as the speaker's identity and emotional state. These attributes can be used for malicious purposes. With the development of virtual assistants, a new generation of privacy threats…
This paper explores the intersection of privacy, cybersecurity, and environmental impacts, specifically energy consumption and carbon emissions, in cloud-based office solutions. We hypothesise that solutions that emphasise privacy and…
Given the ubiquity of mobile applications (apps) in daily lives, understanding and reflecting end-users' human values (e.g., transparency, privacy, social recognition etc.) in apps has become increasingly important. Violations of end users'…
Virtual assistants, also known as intelligent conversational systems such as Google's Virtual Assistant and Apple's Siri, interact with human-like responses to users' queries and finish specific tasks. Meanwhile, existing recommendation…