Related papers: Identifying Privacy Concerns in Upcoming Software …
To investigate the level of support and awareness developers possess for dealing with sensitive data in the metaverse, we surveyed developers, consulted legal frameworks, and analyzed API documentation in the metaverse. Our preliminary…
The open-source nature of the Android OS makes it possible for manufacturers to ship custom versions of the OS along with a set of pre-installed apps, often for product differentiation. Some device vendors have recently come under scrutiny…
Software updates are essential to enhance security, fix bugs, and add better features to the existing software. While some users accept software updates, non-compliance remains a widespread issue. While some users accept software updates,…
For the safe sharing pre-trained language models, no guidelines exist at present owing to the difficulty in estimating the upper bound of the risk of privacy leakage. One problem is that previous studies have assessed the risk for different…
The increasing popularity of social media has attracted a huge number of people to participate in numerous activities on a daily basis. This results in tremendous amounts of rich user-generated data. This data provides opportunities for…
Decisions about sharing personal information are not trivial, since there are many legitimate and important purposes for such data collection, but often the collected data can reveal sensitive information about individuals.…
Predicting a mobile app's popularity before its first release can provide developers with a strategic advantage in a competitive marketplace, yet it remains a challenging problem. This study explores the extent to which internal software…
GenAI smartphones, which natively embed generative AI at the system level, are transforming mobile interactions by automating a wide range of tasks and executing UI actions on behalf of users. Their superior capabilities rely on continuous…
Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and…
The Internet of Things' potential for major privacy invasion is a concern. This paper reports on a systematic literature review of privacy-preserving solutions appearing in the research literature and in the media. We analysed proposed…
The exponential growth of collected, processed, and shared data has given rise to concerns about individuals' privacy. Consequently, various laws and regulations have been established to oversee how organizations handle and safeguard data.…
The balance between protecting users' privacy while providing cost-effective devices that are functional and usable is a key challenge in the burgeoning Internet of Things (IoT) industry. While in traditional desktop and mobile contexts the…
Mobile applications are required to give privacy notices to users when they collect or share personal information. Creating consistent and concise privacy notices can be a challenging task for developers. Previous work has attempted to help…
Privacy personas capture the differences in user segments with respect to one's knowledge, behavioural patterns, level of self-efficacy, and perception of the importance of privacy protection. Modelling these differences is essential for…
Machine learning models have demonstrated promising performance in many areas. However, the concerns that they can be biased against specific demographic groups hinder their adoption in high-stake applications. Thus, it is essential to…
Large language models (LLMs) are primarily accessed via commercial APIs, but this often requires users to expose their data to service providers. In this paper, we explore how users can stay in control of their data by using privacy…
Privacy regulations such as the CCPA and GDPR grant individuals rights over their personal data, yet it remains challenging for most users to exercise them in practice due to vague policy interpretation and unapproachable settings on web…
Research software is increasingly recognized as a vital component of the scholarly record. Journals offer authors the opportunity to publish research software papers, but often have different requirements for how these publications should…
Privacy policies are long, complex documents that end-users seldom read. Privacy labels aim to ameliorate these issues by providing succinct summaries of salient data practices. In December 2020, Apple began requiring that app developers…
The generation of privacy-preserving synthetic datasets is a promising avenue for overcoming data scarcity in medical AI research. Post-hoc privacy filtering techniques, designed to remove samples containing personally identifiable…