While symbolic execution (SE) can discover software vulnerabilities, it has received limited practical adoption. A key barrier is that SE requires human expertise to understand the program’s state and prioritize paths to analyze. Traditionally, users controlled SE through programmatic API calls, but recent tooling now implements graphical user interfaces (GUI). However, it is unclear how these new features affect human-SE performance. To understand this impact, we conducted a controlled experiment where 24 vulnerability discovery experts were tasked with analyzing a binary using an SE tool with either API or GUI-based features. From this study, we identify (1) experts’ SE process, and (2) the impact of GUI-based features on human-SE performance. Then we propose recommendations to improve SE tool design.

Access Control (AC) remains one of the fundamental paradigms of computer security due to its potential to mitigate serious threats by restricting access to sensitive resources within emerging technologies. However, despite decades of research, the life-cycle, i.e., specification, evaluation, and enforcement, of AC policies in modern cyber-infrastructures remains incomplete, inaccurate, and unverified, which largely decreases their effectiveness and efficiency to counteract emerging threats and vulnerabilities.

Research Computing Infrastructures (RCIs) inte-grate high-performance computing, advanced data storage solutions, and sophisticated network protocols, connecting people, data, and computing resources to facilitate scientific collaboration in today's data-driven world. Access control is essential in such highly collaborative environments to prevent resource misutilization, safeguard data integrity, and allocate resources effectively, thereby enabling secure and trusted in-teractions among different users. However, unlocking the full potential of RCIs for collaborative research through effective access control requires more than technological exploration-it demands a deep, human-centered understanding of the stakeholders who operate and utilize these systems. In this paper, we present the first qualitative study that explores the human dimensions of RCI interactions, drawing insights from 24 key stakeholders, including researchers and system administrators, across 12 research institutions to ex-amine the collaborative practices, challenges, and needs with a focus on access control. Our findings reveal operational complexities and project-specific, trust-based resource-sharing dynamics, highlighting tensions between security and usability. Based on these insights, we provide stakeholder-driven rec-ommendations and requirements for adaptive, user-centered access control for RCIs, laying the groundwork for advancing human-centered security practices in RCIs.

The education technology (EdTech) landscape is expanding rapidly in higher education institutes (HEIs). This growth brings enormous complexity. Protecting the extensive data collected by these tools is crucial for HEIs as data breaches and misuses can have dire security and privacy consequences for the data subjects, particularly students, who are often compelled to use these tools. This urges an in-depth understanding of HEI and EdTech vendor dynamics, which is largely understudied.

The complex and diverse nature of software systems necessitates a careful manual approach to unveil vulnerabilities, involving deep analysis, creative problem-solving, and specialized expertise. Like all complex tasks, it’s susceptible to mistakes stemming from cognitive limitations and behavioral factors that hinder optimal performance. Although there are significant research efforts focused on vulnerability discovery, little attention has been given to comprehending mistakes within the process. Understanding these mistakes could pave the way for better-designed education programs and automated tools, aiming to mitigate and prevent potential mistakes and enhance the efficiency of vulnerability research.In this paper, we leverage social media, specifically YouTube, to examine mistakes made by security content creators exploiting vulnerabilities in CTF-style challenges. Analyzing 30 screencasts from 11 hackers, we identified 124 distinct issues and investigated their types, underlying causes, and time investments. Additionally, we delved into the cognitive and behavioral aspects associated with these issues.

With over 1.5 million content creators, OnlyFans is one of the fastest growing subscription-based social media platforms. The platform is primarily associated with sexual content. Thus, OnlyFans creators are uniquely positioned at the intersection of professional social media content creation and sex work. While the motivations of experienced sex workers to adopt OnlyFans have been studied, in this work we seek to understand the motivations of creators who had not previously done sex work. Through a qualitative interview study of 22 U.S.-based OnlyFans creators, we find that beyond the typical motivations for pursuing gig work (e.g., flexibility, autonomy), our participants were motivated by three key factors: (1) societal visibility and mainstream acceptance of OnlyFans; (2) platform design and affordances such as boundary-setting with clients, privacy from the public, and content archives; and (3) the pandemic, as OnlyFans provided an enormous opportunity to overcome lockdown-related issues.

The academic computer security community has traditionally adopted peer review as an integral part of scientific publishing and dissemination, in a process that grows organically and nourishes itself by internal communications and intuitions, rather than repeatable experiments and investigations. Recently, key community members have shared a series of concerns regarding this process in public. To support or disprove some of these concerns, this paper presents the first qualitative study to examine the peer review process in the computer security field. Through semi-structured interviews (n=21) with Program Committee members, we systematically collect the reviewers’ insights on how papers are evaluated in top-tier security conferences and investigate their concerns regarding the current security peer review system. Based on the collected data, we identify several issues in the security review system: whereas some have been previously observed by the community (e.g., the randomness in reviewers’ decisions), others (e.g., reviewers have much more diverse and concrete opinions on the metrics of rejecting papers) have been observed for the first time in our study. Finally, through a series of recommendations, we aim to encourage the collaborative establishment of community norms that will significantly improve the security peer review process.

Organizations, such as companies and governments, created Security Operations Centers (SOCs) to defend against computer security attacks. SOCs are central defense groups that focus on security incident management with capabilities such as monitoring, preventing, responding, and reporting. They are one of the most critical defense components of a modern organization's defense. Despite their critical importance to organizations, and the high frequency of reported security incidents, only a few research studies focus on problems specific to SOCs. In this study, to understand and identify the issues of SOCs, we conducted 18 semi-structured interviews with SOC analysts and managers who work for organizations from different industry sectors. Through our analysis of the interview data, we identified technical and non-technical issues that exist in SOC. Moreover, we found inherent disagreements between SOC managers and their analysts that, if not addressed, could entail a risk to SOC efficiency and effectiveness. We distill these issues into takeaways that apply both to future academic research and to SOC management. We believe that research should focus on improving the efficiency and effectiveness of SOCs.