Software supply chain security is an essential area of cybersecurity, as shown by attacks such as the XZ Utils incident in 2024.Software Bills of Materials (SBOMs) were introduced to keep track of the supply chain of a software artifact.They have been brought to widespread attention in 2021 through US Executive Order 14028.The EU will make SBOMs mandatory by 2027 with their Cyber Resilience Act from 2024.In contrast to these demands for SBOMs through legislation, practitioners struggle to make real use of them.Multiple recent studies have concluded that adoption of SBOMs and their integration into security processes are facing various challenges.At the same time, accuracy and correctness problems of SBOMs generated by wide-spread tools have been shown.Based on this situation, the dissertation research is dedicated to the research question:What benefit do SBOMs provide and what further benefit can they potentially provide for supply chain security?In order to answer, this research description introduces four intended contributions:(1) First, all knowledge about the history of SBOMs and related concepts in Computer Science is systematized.(2) Second, an SBOM usage model that provides an abstract view on the software supply chain as well as actors involved in it is developed.The goal of the model is to give a theoretical foundation for making practical use of SBOMs.(3) Third, with BOM2VULN an analysis of current tools that map vulnerabilities to SBOMs is conducted, potentially including the introduction of a new tool for this task.The goal is to provide security engineers with a means of quickly finding vulnerabilities and assessing their relevance.(4) Lastly, the SBOM Nutri Score is proposed including an evaluation.The score helps practitioners to evaluate the software supply chain risk of third party code they use or intend to use. CCS Concepts• Security and privacy → Vulnerability

Many illusion and interaction techniques in Virtual Reality (VR) rely on Hand Redirection (HR), which has proved to be effective as long as the introduced offsets between the position of the real and virtual hand do not noticeably disturb the user experience. Yet calibrating HR offsets is a tedious and time-consuming process involving psychophysical experimentation, and the resulting thresholds are known to be affected by many variables—limiting HR’s practical utility. As a result, there is a clear need for alternative methods that allow tailoring HR to the perceptual boundaries of individual users. We conducted an experiment with 18 participants combining movement, eye gaze and EEG data to detect HR offsets Below, At, and Above individuals’ detection thresholds. Our results suggest that we can distinguish HR At and Above from no HR. Our exploration provides a promising new direction with potentially strong implications for the broad field of VR illusions.

Achieving temporal synchrony between sensory modalities is crucial for natural perception of object interaction in virtual reality (VR). While subjective questionnaires are currently used to evaluate users’ VR experiences, leveraging behavior and psychophysiological responses can provide additional insights. We investigated motion and ocular behavior as discriminators between realistic and unrealistic object interactions. Participants grasped and placed a virtual object while experiencing sensory feedback that either matched their expectations or occurred too early. We also explored visual-only feedback vs. combined visual and haptic feedback. Due to technological limitations, a condition with delayed feedback was added post hoc . Gaze-based metrics revealed discrimination between high- and low-feedback realism. Increased interaction uncertainty was associated with longer fixations on the avatar hand and temporal shifts in the gaze–action relationship. Our findings enable real-time evaluation of users’ perception of realism in interactions. They facilitate the optimization of interaction realism in virtual environments and beyond.

OBJECTIVE: Mixed-Reality (XR) technologies promise a user experience (UX) that rivals the interactive experience with the real-world. The key facilitators in the design of such a natural UX are that the interaction has zero lag and that users experience no excess mental load. This is difficult to achieve due to technical constraints such as motion-to-photon latency as well as false-positives during gesture-based interaction. METHODS: In this paper, we explored the use of physiological features to model the user's intent to interact with a virtual reality (VR) environment. Accurate predictions about when users want to express an interaction intent could overcome the limitations of an interactive device that lags behind the intention of a user. We computed time-domain features from electroencephalography (EEG) and electromyography (EMG) recordings during a grab-and-drop task in VR and cross-validated a Linear Discriminant Analysis (LDA) for three different combinations of (1) EEG, (2) EMG and (3) EEG-EMG features. RESULTS & CONCLUSION: We found the classifiers to detect the presence of a pre-movement state from background idle activity reflecting the users' intent to interact with the virtual objects (EEG: 62 % ± 10 %, EMG: 72 % ± 9 %, EEG-EMG: 69 % ± 10 %) above simulated chance level. The features leveraged in our classification scheme have a low computational cost and are especially useful for fast decoding of users' mental states. Our work is a further step towards a useful classification of users' intent to interact, as a high temporal resolution and speed of detection is crucial. This facilitates natural experiences through zero-lag adaptive interfaces.

During listening to music, the brain expects specific acoustic events based on learned musical rules. During music performance expectancy is additionally created based on motor action by linking keypresses to their sounds. We investigated EEG (Electroencephalography) signals to auditory expectancy violations in piano performance and perception. In our study, pianists experienced manipulations of different acoustic features, such as pitch and loudness, during playing and listening to piano sequences. We found that manipulations during performance elicited deflections with stronger amplitudes compared to manipulations during perception indicating that the action of producing sounds strengthens auditory expectancy. Loudness manipulations, violating musical regularity, elicited deflections with smaller latencies compared to pitch manipulations, which violate harmonic expectancy, suggesting that the brain processes expectancy violations of distinct acoustic features in a different way. These EEG signatures may prove useful for applications in intelligent music interfaces by providing information about sensory-motor accuracy.

Designing immersion is the key challenge in virtual reality; this challenge has driven advancements in displays, rendering and recently, haptics. To increase our sense of physical immersion, for instance, vibrotactile gloves render the sense of touching, while electrical muscle stimulation (EMS) renders forces. Unfortunately, the established metric to assess the effectiveness of haptic devices relies on the user's subjective interpretation of unspecific, yet standardized, questions.