Everyday talk is often treated as casual chatter, yet it plays a crucial role in how people acquire and share knowledge. Typically, cybersecurity practices are informed by formal training, but they often overlook the impact of social exchanges. This paper investigates how informal conversations can act as a socio-technical mechanism for shaping cybersecurity awareness and practices. We conducted an online survey (N=215) where participants described recent discussions about cybersecurity, including who was involved, where they took place, and what triggered them. Quantitative and thematic analysis revealed common contexts, social settings, and topics. Most conversations occurred spontaneously in private environments, with personal experiences being the most frequent trigger. We contribute empirical insights on informal security conversations to inform the design of human-centered technologies that surface and mediate security-related discussions in everyday contexts, to ensure implicit and continuous security awareness.

Public Security User Interfaces (PSUIs) are a relative new approach to increasing cybersecurity awareness and promoting secure behavior in public and semi-public spaces. Unlike traditional methods such as emails or mobile apps, PSUIs use dynamic content and interactive elements to engage users in real time and promote proactive security measures. This paper explores the design and implementation of a previously introduced concept of PSUIs through a use case, driving awareness and adoption of password managers. Drawing insights from a pilot study (N=5) and a main study (N=25), we identify a set of implications for designing PSUIs that prioritize engagement strategies, actionable outcomes, accessibility and inclusivity, and normalizing mistakes. Key challenges include content adaptation, audience dynamics, and privacy. By bridging the gap between public engagement and cybersecurity education, this work lays the foundation for future research and practical implementation of PSUIs as a tool to foster secure digital habits.

Extended Reality (XR) systems bring arrays of sensors closer to the user’s body, enabling the collection of extensive user and contextual data, from motion and biometrics to behavioral analytics, that users might not be aware they are sharing. This poses significant risks to users’ privacy. Yet, despite the immersive and dynamic nature of XR, most platforms still rely on static, text-based privacy mechanisms inherited from traditional 2D interfaces. We propose a new paradigm of continuous consent in XR, where privacy decisions unfold as a relational, context-aware, and renegotiable process embedded in the experience – not a single consent event. To this end, we propose a Multi-Layered Privacy Framework spanning five interdependent layers: regulatory compliance, technical implementation, permission models, user experience, and user perception and cognition. We then introduce the User Privacy Journey Model, which operationalizes the framework as a sequential user pathway: from onboarding and contextual prompts to in-experience control and post-session review, along with the XR Privacy Checklist to support practical adoption. By rethinking consent as a continuous journey, we present a new paradigm for XR privacy, one that opens a new research perspective on what "informed" consent means in immersive environments where the boundaries between self, system, and space are increasingly blurred.

Mobile Augmented Reality (AR) applications leverage various sensors to provide immersive user experiences. However, their reliance on diverse data sources introduces significant privacy challenges. This paper investigates user perceptions and understanding of privacy permissions in mobile AR apps through an analysis of existing applications and an online survey of 120 participants. Findings reveal common misconceptions, including confusion about how permissions relate to specific AR functionalities (e.g., location and measurement of physical distances), and misinterpretations of permission labels (e.g., conflating camera and gallery access). We identify a set of actionable implications for designing more usable and transparent privacy mechanisms tailored to mobile AR technologies, including contextual explanations, modular permission requests, and clearer permission labels. These findings offer actionable guidance for developers, researchers, and policymakers working to enhance privacy frameworks in mobile AR.

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Acoustic levitation has recently demonstrated the ability to create volumetric content by trapping and quickly moving particles along reference paths to reveal shapes in mid-air. However, the problem of specifying physically feasible trap trajectories to display desired shapes remains unsolved. Even if only the final shape is of interest to the content creator, the trap trajectories need to determine where and when the traps need to be, for the particle to reveal the intended shape. We propose OptiTrap , the first structured numerical approach to compute trap trajectories for acoustic levitation displays. Our approach generates trap trajectories that are physically feasible and nearly time-optimal, and reveal generic mid-air shapes, given only a reference path (i.e., a shape with no time information). We provide a multi-dimensional model of the acoustic forces around a trap to model the trap-particle system dynamics and compute optimal trap trajectories by formulating and solving a non-linear path following problem. We formulate our approach and evaluate it, demonstrating how OptiTrap consistently produces feasible and nearly optimal paths, with increases in size, frequency, and accuracy of the shapes rendered, allowing us to demonstrate larger and more complex shapes than ever shown to date.

Mid-air haptic interfaces have several advantages - the haptic information is delivered directly to the user, in a manner that is unobtrusive to the immediate environment. They operate at a distance, thus easier to discover; they are more hygienic and allow interaction in 3D. We validate, for the first time, in a preliminary study with sighted and a user study with blind participants, the use of mid-air haptics for conveying Braille. We tested three haptic stimulation methods, where the haptic feedback was either: a) aligned temporally, with haptic stimulation points presented simultaneously (Constant); b) not aligned temporally, presenting each point independently (Point-By-Point); or c) a combination of the previous methodologies, where feedback was presented Row-by-Row. The results show that mid-air haptics is a viable technology for presenting Braille characters, and the highest average accuracy (94% in the preliminary and 88% in the user study) was achieved with the Point-by-Point method.

We present the Levitation Simulator, a system that enables researchers and designers to iteratively develop and prototype levitation interface ideas in Virtual Reality. This includes user tests and formal experiments. We derive a model of the movement of a levitating particle in such an interface. Based on this, we develop an interactive simulation of the levitation interface in VR, which exhibits the dynamical properties of the real interface. The results of a Fitts' Law pointing study show that the Levitation Simulator enables performance, comparable to the real prototype. We developed the first two interactive games, dedicated for levitation interfaces: LeviShooter and BeadBounce, in the Levitation Simulator, and then implemented them on the real interface. Our results indicate that participants experienced similar levels of user engagement when playing the games, in the two environments. We share our Levitation Simulator as Open Source, thereby democratizing levitation research, without the need for a levitation apparatus.

We present LeviCursor, a method for interactively moving a physical, levitating particle in 3D with high agility. The levitating object can move continuously and smoothly in any direction. We optimize the transducer phases for each possible levitation point independently. Using precomputation, our system can determine the optimal transducer phases within a few microseconds and achieves round-trip latencies of 15 ms. Due to our interpolation scheme, the levitated object can be controlled almost instantaneously with sub-millimeter accuracy. We present a particle stabilization mechanism which ensures that the levitating particle is always in the main levitation trap. Lastly, we conduct the first Fitts' law-type pointing study with a real 3D cursor, where participants control the movement of the levitated cursor between two physical targets. The results of the user study demonstrate that using LeviCursor, users reach performance comparable to that of a mouse pointer.