相关论文: Security, Privacy and Safety Risk Assessment for V…
Current LLM-based conversational recommender systems (CRS) primarily optimize recommendation accuracy and user satisfaction. We identify an underexplored vulnerability in which recommendation outputs may negatively impact users by violating…
In contemporary training for industrial manufacturing, reconciling theoretical knowledge with practical experience continues to be a significant difficulty. As companies transition to more intricate and technology-oriented settings,…
Advances in machine learning (ML) in recent years have enabled a dizzying array of applications such as data analytics, autonomous systems, and security diagnostics. ML is now pervasive---new systems and models are being deployed in every…
The rapid advancement of machine learning (ML) has led to its increasing integration into cyber-physical systems (CPS) across diverse domains. While CPS offer powerful capabilities, incorporating ML components introduces significant safety…
This paper presents a comprehensive benchmarking suite tailored to offline safe reinforcement learning (RL) challenges, aiming to foster progress in the development and evaluation of safe learning algorithms in both the training and…
Classification algorithms face difficulties when one or more classes have limited training data. We are particularly interested in classification trees, due to their interpretability and flexibility. When data are limited in one or more of…
In the rapidly evolving landscape of blockchain technology, ensuring the integrity and security of data is paramount. This study delves into the security aspects of Merkle Trees, a fundamental component in blockchain architectures, such as…
Virtual Reality (VR) is a promising tool for interview training, yet the psychological dynamics of group interviews, such as social comparison, remain underexplored. We investigate this phenomenon by developing an immersive VR group…
Social Virtual Reality (VR) platforms have surged in popularity, yet their security risks remain underexplored. This paper presents four novel UI attacks that covertly manipulate users into performing harmful actions through deceptive…
Virtual Reality (VR) is an exciting new consumer technology which offers an immersive audio-visual experience to users through which they can navigate and interact with a digitally represented 3D space (i.e., a virtual world) using a…
The rise of social networking platforms has amplified privacy threats as users increasingly share sensitive information across profiles, content, and social connections. We present a Comprehensive Privacy Risk Scoring (CPRS) framework that…
While the safety risks of image-based large language models (Image LLMs) have been extensively studied, their video-based counterparts (Video LLMs) remain critically under-examined. To systematically study this problem, we introduce…
Immersive virtual reality (VR) enables controlled tests of how emotional context distorts subjective time, yet findings remain mixed. Fifty-seven adults explored three five-minute VR environments (tranquil garden, neutral room, threatening…
The integration of vision-language models (VLMs) is driving a new generation of embodied agents capable of operating in human-centered environments. However, as deployment expands, these systems face growing safety risks, particularly when…
The rising interest in Virtual Reality (VR) technology has sparked a desire to create immersive learning platforms capable of handling various tasks across environments. Through immersive interfaces, users can engage deeply with virtual…
This paper attempts to strengthen the pursued research on social engineering (SE) threat identification, and control, by means of the author's illustrated classification, which includes attack types, determining the degree of possible harm…
Reinforcement Learning (RL) algorithms have achieved remarkable performance in decision making and control tasks due to their ability to reason about long-term, cumulative reward using trial and error. However, during RL training, applying…
Robots are typically not created with security as a main concern. Contrasting to typical IT systems, cyberphysical systems rely on security to handle safety aspects. In light of the former, classic scoring methods such as the Common…
In the last decade, a lot of effort has been put into securing software application during development in the software industry. Software security is a research field in this area which looks at how security can be weaved into software at…
Deep learning (DL)-based automated cybersickness detection methods, along with adaptive mitigation techniques, can enhance user comfort and interaction. However, recent studies show that these DL-based systems are susceptible to adversarial…