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Online community research routinely poses minimal risk to individuals, but does the same hold true for online communities? In response to high-profile breaches of online community trust and increased debate in the social computing research…
Integrated safety and security assurance for complex systems is difficult for many technical and socio-technical reasons such as mismatched processes, inadequate information, differing use of language and philosophies, etc.. Many…
The proliferation of mobile applications and the subsequent sharing of personal data with service and application providers have given rise to substantial privacy concerns. Application marketplaces have introduced mechanisms to conform to…
Cyber security is considered a necessity for anyone in todays modern world. Awareness of cyber security standards and best practices have become mandatory to safeguard ones child in this day and age. High schoolers today do not understand…
Compact user representations (such as embeddings) form the backbone of personalization services. In this work, we present a new theoretical framework to measure re-identification risk in such user representations. Our framework, based on…
Authentication is crucial to confirm that an individual or entity trying to perform an action is actually who or what they claim to be. In dynamic environments such as the Internet of Things (IoT), Internet of Vehicles (IoV), healthcare,…
Cameras capture images that are essential for many safety-critical tasks. To process these images, a complex pipeline with multiple layers is used. Security attacks on this pipeline can severely affect passenger safety and system…
Social media platforms have enabled individuals suffering from mental illnesses to share their lived experiences and find the online support necessary to cope. However, many users fail to receive genuine clinical support, thus exacerbating…
Online propaganda detection pipelines expose measurable privacy risks at multiple stages including data collection, feature extraction, and model inference. We conduct a structured analysis of $162$ peer-reviewed studies and formalize the…
We propose a harm-centric conceptualization of privacy that asks: What harms from personal data use can privacy prevent? The motivation behind this research is limitations in existing privacy frameworks (e.g., Contextual Integrity) to…
Nowadays, Social Networks have become an essential communication tools producing a large amount of information about their users and their interactions, which can be analysed with Data Mining methods. In the last years, Social Networks are…
In today's dynamic ICT environments, the ability to control users' access to resources becomes ever important. On the one hand, it should adapt to the users' changing needs; on the other hand, it should not be compromised. Therefore, it is…
Artificial Intelligence (AI) systems introduce unprecedented privacy challenges as they process increasingly sensitive data. Traditional privacy frameworks prove inadequate for AI technologies due to unique characteristics such as…
Behavioral sensing technologies are rapidly evolving across a range of well-being applications. Despite its potential, concerns about the responsible use of such technology are escalating. In response, recent research within the sensing…
Accurately analyzing and modeling online browsing behavior play a key role in understanding users and technology interactions. In this work, we design and conduct a user study to collect browsing data from 31 participants continuously for…
Large language models (LLMs) typically generate identical or similar responses for all users given the same prompt, posing serious safety risks in high-stakes applications where user vulnerabilities differ widely. Existing safety…
Internet Service Providers (ISPs) and individual users of Internet of Things (IoT) play a vital role in securing IoT. However, encouraging them to do so is hard. Our study investigates ISPs' and individuals' attitudes towards the security…
Communicating anonymously comes at a cost - and large communities have been in a constant tug-of-war between the development of faster protocols, and the improvement of security analyses. Thereby more intricate privacy goals emerged and…
Algorithmic risk assessment tools are now commonplace in public sector domains such as criminal justice and human services. These tools are intended to aid decision makers in systematically using rich and complex data captured in…
In this work we present the first holistic survey of the agentic security landscape, structuring the field around three fundamental pillars: Applications, Threats, and Defenses. We provide a comprehensive taxonomy of over 160 papers,…