How Interactions Influence Users' Security Perception of Virtual Reality Authentication?

Users readily embrace the rapid advancements in virtual reality (VR) technology within various everyday contexts, such as gaming, social interactions, shopping, and commerce. In order to facilitate transactions and payments, VR systems require access to sensitive user data and assets, which consequently necessitates user authentication. However, there exists a limited understanding regarding how users' unique experiences in VR contribute to their perception of security. In our study, we adopt a research approach known as ``technology probe'' to investigate this question. Specifically, we have designed probes that explore the authentication process in VR, aiming to elicit responses from participants from multiple perspectives. These probes were seamlessly integrated into the routine payment system of a VR game, thereby establishing an organic study environment. Through qualitative analysis, we uncover the interplay between participants' interaction experiences and their security perception. Remarkably, despite encountering unique challenges in usability during VR interactions, our participants found the intuitive virtualized authentication process beneficial and thoroughly enjoyed the immersive nature of VR. Furthermore, we observe how these interaction experiences influence participants' ability to transfer their pre-existing understanding of authentication into VR, resulting in a discrepancy in perceived security. Moreover, we identify users' conflicting expectations, encompassing their desire for an enjoyable VR experience alongside the assurance of secure VR authentication. Building upon our findings, we propose recommendations aimed at addressing these expectations and alleviating potential conflicts

Where to Recruit for Security Development Studies: Comparing Six Software Developer Samples

Studying developers is an important aspect of usable security and privacy research. In particular, studying security development challenges such as the usability of security APIs, the secure use of information sources during development or the effectiveness of IDE security plugins raised interest in recent years. However, recruiting skilled participants with software development experience is particularly challenging, and it is often not clear what security researchers can expect from certain participant samples, which can make research results hard to compare and interpret. Hence, in this work, we study for the first time opportunities and challenges of different platforms to recruit participants with software development experience for security development studies. First, we identify popular recruitment platforms in 59 papers. Then, we conduct a comparative online study with 706 participants based on self-reported software development experience across six recruitment platforms. Using an online questionnaire, we investigate participants’ programming and security experiences, skills and knowledge. We find that participants across all samples report rich general software development and security experience, skills, and knowledge. Based on our results, we recommend developer recruitment from Upwork for practical coding studies and Amazon MTurk along with a pre-screening survey to reduce additional noise for larger studies. Both of these, along with Freelancer, are also recommended for security studies. We conclude the paper by discussing the impact of our results on future security development studies

Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twitter

Many researchers have studied non-expert users’ perspectives of cyber security and privacy aspects of computing devices at home, but their studies are mostly small-scale empirical studies based on online surveys and interviews and limited to one or a few specific types of devices, such as smart speakers. This paper reports our work on an online social media analysis of a large-scale Twitter dataset, covering cyber security and privacy aspects of many different types of computing devices discussed by non-expert users in the real world. We developed two new machine learning based classifiers to automatically create the Twitter dataset with 435,207 tweets posted by 337,604 non-expert users in January and February of 2019, 2020 and 2021. We analyzed the dataset using both quantitative (topic modeling and sentiment analysis) and qualitative analysis methods, leading to various previously unknown findings. For instance, we observed a sharp (more than doubled) increase of non-expert users’ tweets on cyber security and privacy during the pandemic in 2021, compare to in the pre-COVID years (2019 and 2020). Our analysis revealed a diverse range of topics discussed by non-expert users, including VPNs, Wi-Fi, smartphones, laptops, smart home devices, financial security, help-seeking, and roles of different stakeholders. Overall negative sentiment was observed across almost all topics in all the three years. Our results confirm the multi-faceted nature of non-expert users’ perspectives on cyber security and privacy and call for more holistic, comprehensive and nuanced research on their perspectives

User Experience Design for Cybersecurity & Privacy: addressing user misperceptions of system security and privacy

The increasing magnitude and sophistication of malicious cyber activities by various threat actors poses major risks to our increasingly digitized and inter-connected societies. However, threats can also come from non-malicious users who are being assigned too complex security or privacy-related tasks, who are not motivated to comply with security policies, or who lack the capability to make good security decisions. This thesis posits that UX design methods and practices are necessary to complement security and privacy engineering practices in order to (1) identify and address user misperceptions of system security and privacy; and (2) inform the design of secure systems that are useful and appealing from end-users’ perspective. The first research objective in this thesis is to provide new empirical accounts of UX aspects in three distinct contexts that encompass security and privacy considerations, namely: cyber threat intelligence, secure and private communication, and digital health technology. The second objective is to empirically contribute to the growing research domain of mental models in security and privacy by investigating user perceptions and misperceptions in the afore-mentioned contexts. Our third objective is to explore and propose methodological approaches to incorporating users’ perceptions and misperceptions in the socio-technical security analyses of systems. Qualitative and quantitative user research methods with experts as well as end users of the applications and systems under investigation were used to achieve the first two objectives. To achieve the third objective, we also employed simulation and computational methods. Cyber Threat Intelligence: CTI sharing platforms Reporting on a number of user studies conducted over a period of two years, this thesis offers a unique contribution towards understanding the constraining and enabling factors of security information sharing within one of the leading CTI sharing platforms, called MISP. Further, we propose a conceptual workflow and toolchain that would seek to detect user (mis)perceptions of key tasks in the context of CTI sharing, such as verifying whether users have an accurate comprehension of how far information travels when shared in a CTI sharing platform, and discuss the benefits of our socio-technical approach as a potential security analysis tool, simulation tool, or educational / training support tool. Secure & Private Communication: Secure Email We propose and describe multi-layered user journeys, a conceptual framework that serves to capture the interaction of a user with a system as she performs certain goals along with the associated user beliefs and perceptions about specific security or privacy-related aspects of that system. We instantiate the framework within a use case, a recently introduced secure email system called p≡p, and demonstrate how the approach can be used to detect misperceptions of security and privacy by comparing user opinions and behavior against system values and objective technical guarantees offered by the system. We further present two sets of user studies focusing on the usability and effectiveness of p≡p’s security and privacy indicators and their traffic-light inspired metaphor to represent different privacy states and guarantees. Digital Health Technology: Contact Tracing Apps Considering human factors when exploring the adoption as well as the security and privacy aspects of COVID-19 contact tracing apps is a timely societal challenge as the effectiveness and utility of these apps highly depend on their widespread adoption by the general population. We present the findings of eight focus groups on the factors that impact people’s decisions to adopt, or not to adopt, a contact tracing app, conducted with participants living in France and Germany. We report how our participants perceived the benefits, drawbacks, and threat model of the contact tracing apps in their respective countries, and discuss the similarities and differences between and within the study groups. Finally, we consolidate the findings from these studies and discuss future challenges and directions for UX design methods and practices in cybersecurity and digital privacy