相关论文: A First Look at Privacy Risks of Android Task-exec…
Increasing interest in securing the Android ecosystem has spawned numerous efforts to assist app developers in building secure apps. These efforts have resulted in tools and techniques capable of detecting vulnerabilities (and malicious…
The proliferation of AI has sparked privacy concerns related to training data, model interfaces, downstream applications, and more. We interviewed 25 AI developers based in Europe to understand which privacy threats they believe pose the…
Eye tracking is routinely being incorporated into virtual reality (VR) systems. Prior research has shown that eye tracking data, if exposed, can be used for re-identification attacks. The state of our knowledge about currently existing…
The widespread adoption of conversational AI platforms has introduced new security and privacy risks. While these risks and their mitigation strategies have been extensively researched from a technical perspective, users' perceptions of…
The current "notice and consent" paradigm is broken: consent dialogues are often manipulative, and users cannot realistically read or understand every privacy policy. While recent LLM-based tools empower users seeking active control, many…
The rise of Large Language Models (LLMs) has revolutionized Graphical User Interface (GUI) automation through LLM-powered GUI agents, yet their ability to process sensitive data with limited human oversight raises significant privacy and…
Voice Assistant (VA) in smartphones has become very popular with millions of users nowadays. A key trend is the rise of custom VA embedding, which enables users to perform the customized tasks of their favorite app through voice control.…
Mobile Health (mHealth) applications have become a crucial part of health monitoring and management. However, the proliferation of these applications has also raised concerns over the privacy and security of Personally Identifiable…
Recent works have identified a gap between research and practice in artificial intelligence security: threats studied in academia do not always reflect the practical use and security risks of AI. For example, while models are often studied…
Privacy policies are intended to inform users about how software systems collect and handle data, yet they often remain vague or incomplete. This paper presents an empirical study of patterns in log-related statements within privacy…
Mobile devices are used more and more in everyday life. They are our cameras, wallets, and keys. Basically, they embed most of our private information in our pocket. For this and other reasons, mobile devices, and in particular the software…
Android apps can hold secret strings of themselves such as cloud service credentials or encryption keys. Leakage of such secret strings can induce unprecedented consequences like monetary losses or leakage of user private information. In…
Although there are over 1,600,000 third-party Android apps in the Google Play Store, little has been conclusively shown about how their individual (and collective) permission usage has evolved over time. Recently, Android 6 overhauled the…
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…
This paper investigates the privacy and usability of AI-enabled smart devices commonly used by youth, focusing on Google Home Mini, Amazon Alexa, and Apple Siri. While these devices provide convenience and efficiency, they also raise…
Foundation models--such as GPT, CLIP, and DINO--have achieved revolutionary progress in the past several years and are commonly believed to be a promising approach for general-purpose AI. In particular, self-supervised learning is adopted…
Mobile gaming applications (apps) have become increasingly pervasive, including a growing number of games designed for children. Despite their popularity, these apps often integrate complex analytics, advertising, and attribution…
With the rapid development of artificial intelligence, large language models (LLMs) have made remarkable advancements in natural language processing. These models are trained on vast datasets to exhibit powerful language understanding and…
The widespread adoption of voice-activated systems has modified routine human-machine interaction but has also introduced new vulnerabilities. This paper investigates the susceptibility of automatic speech recognition (ASR) algorithms in…
Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalised experiences to socialize, work, and play in self-sustaining and hyper-spatio-temporal virtual world(s). The…