This poster presents a methodology for evaluating course syllabi using large language models and semantic embeddings. We demonstrate this approach by analyzing 141 cybersecurity syllabi from top-ranked American institutions. Using the intfloat/e5-base-v2 embedding model, syllabus text was mapped to competencies in the National Institute of Standards and Technology's (NIST) National Initiative for Cybersecurity Education Framework (NICE Framework). Cybersecurity was chosen as the domain due to the field's workforce shortage and the existence of the NICE Framework as a standardized taxonomy. This research illustrates how large language models can support curriculum analysis by automating the alignment of educational materials to competency frameworks, offering a scalable approach for other disciplines.

The advent of autonomous vehicles (AVs) represents a transformative shift in transportation, promising to redefine mobility and alter our interaction with vehicles. Understanding public perceptions of AVs is crucial, as it influences the adoption and integration of this technology into society. This research conducts a comprehensive investigation into the factors that influence people’s attitudes toward AVs, examining the associated benefits and concerns, as well as the extent of trust placed in this emerging technology. The primary objective is to gain a deeper understanding of the elements that contribute to human-machine trust in the context of AVs. The findings reveal a consistent pattern in the propensity to trust AVs and concerns regarding performance failures, both at individual and societal levels. From a societal perspective, enhanced locomotion independence is the primary benefit of AV deployment, contributing to increased accessibility and reduced reliance on conventional transportation systems. At the individual level, increased free time emerges as the foremost advantage. These findings provide AV developers and policymakers the critical insight when deploying autonomous vehicle systems.

Avatars as digital portrayals of humans play a pivotal role in fostering embodiment and immersion in virtual reality (VR) environments by providing users with a visual representation of their virtual presence. In the context of human-robot interaction (HRI), understanding the dynamics of trust formation between humans and avatars are essential for successful collaboration and communication. This study methodically investigates the effect of the similarity between players and their avatars on the establishment of trust between human users and robots in a VR environment. Our research implies that enhancing the resemblance of self-avatars boosts trust dynamics in human-robot interactions, yet it doesn’t necessarily foster cooperation. Moreover, this research highlights the importance of designing virtual avatars and robots that can effectively communicate and adapt to user preferences, thereby fostering a more engaging and productive HRI experience in VR environments.

This study explores whether there is a predictive relationship between humans’ ethical perspectives and their trust in autonomous systems (AS). Whether AS can make ethically acceptable decisions, especially in safety-critical situations involving value trade-offs, has become a significant determinant of how humans will trust these systems. However, knowledge about these relation-based trust dimensions is largely absent from the current theoretical framework of human-AS trust. Addressing this gap, this study used MTurk and Qualtrics to perform an online survey that assessed people’s ethical perspectives, trust in automation, and propensity to trust. The results showed that: (1) Significant differences in trust in automation were seen across four ethical perspectives, confirming the predictive relationship between human ethical perspectives and AS trust. (2) There was no significant difference in propensity to trust among ethical orientations. (3) There was a positive but weak association between trust in automation and willingness to trust. The latter two observations jointly show that trust in automation and trust propensity may be regulated by distinct mechanisms. This study has contributed to existing knowledge by (1) validating the predictive relationship between human ethical perspectives and how they trust AS, (2) revealing potential mechanisms underlying such discrepancies, and (3) highlighting how these differences could help the design of trustworthy AS.

Mobile apps have transformed many aspects of clinical practice and are becoming a commonplace in healthcare settings. The recent COVID-19 pandemic has provided the opportunity for such apps to play an important role in reducing the spread of the virus. Several types of COVID-19 apps have enabled healthcare professionals and governments to communicate with the public regarding the pandemic spread, coronavirus awareness, and self-quarantine measures. While these apps provide immense benefits for the containment of the spread, privacy and security of these digital tracing apps are at the center of public debate. To address this gap, we conducted an online survey of a midwestern region in the United State to assess people’s attitudes toward such apps and to examine their privacy and security concerns and preferences. Survey results from 1,550 participants indicate that privacy/security protections and trust play a vital role in people’s adoption of such apps. Furthermore, results reflect users’ preferences wanting to have control over their personal information and transparency on how their data is handled. In addition, personal data protection priorities selected by the participants were surprising and yet revealing of the disconnect between technologists and users. In this article, we present our detailed survey results as well as design guidelines for app developers to develop innovative human-centered technologies that are not only functional but also respectful of social norms and protections of civil liberties. Our study examines users’ preferences for COVID-19 apps and integrates important factors of trust, willingness, and preferences in the context of app development. Through our research findings, we suggest mechanisms for designing inclusive apps’ privacy and security measures that can be put into practice for healthcare-related apps, so that timely adoption is made possible.

The increasing relevance of information assurance in cloud computing has forced governments and stakeholders to turn their attention to Information Technology (IT) security certifications and standards. The introduction of new frameworks such as FedRAMP in the US and C5 in Germany is aimed to raise the level of protection against threats and vulnerabilities unique to cloud computing. However, our in-depth and systematic analyses reveals that these new standards do not bring a radical change in the realm of certifications. Results also shows that the newly developed standards share much of their basis with older, more consolidated standards such as the ISO/IEC 27001 and hence the need for determining the added value. In this study, we provide an overview of ISO/IEC 27001, C5, and FedRAMP while examining their completeness and adequacy in addressing current threats to cloud assurance. We question the level of protection they offer by comparing these three certifications alongside each other. We identify weaknesses in the three frameworks and highlight necessary improvements to meet the security requirements indispensable in relation to the current threat landscape.

To demonstrate compliance with privacy and security principles, information technology (IT) service providers often rely on security standards and certifications. However, the appearance of new service models such as cloud computing has brought new threats to information assurance, weakening the protection that existing standards can provide. In this study, we analyze four highly regarded IT security standards used to assess, improve, and demonstrate information systems assurance and cloud security. ISO/IEC 27001, SOC 2, C5, and FedRAMP are standards adopted worldwide and constantly updated and improved since the first release of ISO in 2005. We examine their adequacy in addressing current threats to cloud security, and provide an overview of the evolution over the years of their ability to cope with threats and vulnerabilities. By comparing the standards alongside each other, we investigate their complementarity, their redundancies, and the level of protection they offer to information stored in cloud systems. We unveil vulnerabilities left unaddressed in the four frameworks, thus questioning the necessity of multiple standards to assess cloud assurance. We suggest necessary improvements to meet the security requirements made indispensable by the current threat landscape.

The development of automated technologies in our daily life has transformed the role of human operators from a controller to a teammate who shares control with automated agents. However, this 'teammate' relationship between humans and automation raises an important but challenging research question regarding the formation of human-agent trust. Considering that the formation of human-agent trust is a dynamic and sophisticated process involving human factors, this study conducted a two-phase online experiment to examine personal influences on users' trust propensity and their trust formation in human-agent interactions. Our findings revealed distinctive personal influences on dispositional trust and the formation of human-agent trust at different stages. We found that users who exhibit higher trust propensities in humans also develop higher trust toward automated agents in initial stages. This study, as the first of its kind, not only fills the gap of knowledge about personal influences on human-agent trust, but also offers opportunities to enhance the future design of automated agent systems.

Given the growing sophistication of cyber attacks, designing a perfectly secure system is not generally possible. Quantitative security metrics are thus needed to measure and compare the relative security of proposed security designs and policies. Since the investigation of security breaches has shown a strong impact of human errors, ignoring the human user in computing these metrics can lead to misleading results. Despite this, and although security researchers have long observed the impact of human behavior on system security, few improvements have been made in designing systems that are resilient to the uncertainties in how humans interact with a cyber system. In this work, we develop an approach for including models of user behavior, emanating from the fields of social sciences and psychology, in the modeling of systems intended to be secure. We then illustrate how one of these models, namely general deterrence theory, can be used to study the effectiveness of the password security requirements policy and the frequency of security audits in a typical organization. Finally, we discuss the many challenges that arise when adopting such a modeling approach, and then present our recommendations for future work.

With the advent of Internet technologies, information privacy has emerged as an important but complicated notion that is difficult to articulate and conceptualize in technological system design. In this study we identify the key baseline factors for designing privacy-enhancing systems from users' perspective. Utilizing Solove's pragmatic approach to investigate global users' conceptualization of information privacy, we identify two indicators that pertain to information privacy: users' need for information control (NIC) and their perceived risks of information misuse (PRIM). We also examined social influences on these indicators, including region, age, and gender. Our results show that users from different regions of the world consider “the ability to stop unauthorized access” as their foremost priority for information control, while they report “the invasion of personal private sphere” as the highest risk for information misuse. We also found that social factors greatly impact these two indicators. For instance, users from different regions exhibit different needs for information control and perceive risks differently. Based on users' NIC and PRIM as well as regional and generational differences, we propose several user-centered design directions for system developers and policy makers to advance privacy-enhancing systems globally.

Privacy has become an emergent concern in today's digital society. Although scholars have defined privacy from different perspectives, it is still a complex and ambiguous concept. The absence of a concrete concept of privacy impedes the development of privacy legislation and policies in a global context. Therefore, a cross-cultural/national understanding of privacy is urgently needed for establishing a global privacy protocol. This empirical study seeks to better understand privacy by exploring public beliefs of privacy in a global context and further investigating socio-cultural influences on these beliefs. First, we explored general global public beliefs of privacy and then analyzed associations among privacy beliefs and socio-cultural factors. We also investigated the important issue of whether the general global public sees privacy as a “human right.” Results show that most participants agreed with concepts of privacy as a right. However, people had more diverse views on privacy as a right not to be annoyed and social norm privacy concepts. Importantly, nearly eighty percent of people believed in privacy as a human right and nearly seventy percent disagreed with privacy as a concern only for those having something to hide. In the era of globalization, our study provides a bottom-up understanding of privacy beliefs that we believe is essential for the development of global privacy regulation and policies.

Many cryptocurrencies have come into existence in recent years, with Bitcoin the most prominent among them. Although its short history has been volatile, the virtual currency maintains a core group of committed users. This paper presents an exploratory analysis of Bitcoin users. As a virtual currency and peer-to-peer payment system, Bitcoin may signal future challenges to state oversight and financial powers through its decentralized structure and offer of instantaneous transactions with relative anonymity. Very little is known about the users of Bitcoin, however. Utilizing publicly available survey data of Bitcoin users, this analysis explores the structure of the Bitcoin community in terms of wealth accumulation, optimism about the future of Bitcoin, and themes that attract users to the cryptocurrency. Results indicate that age, time of initial use, geographic location, mining status, engaging online discourse, and political orientation are all relevant factors that help explain various aspects of Bitcoin wealth, optimism, and attraction.