Collegiate student-athletes train and compete in a dense data ecology where information about their bodies and performances circulates among coaches, staff, and fans. To understand how student-athletes themselves engage with this data, we conducted interviews with 20 student-athletes, identifying four modes of engagement: 1) performance-directive, executing training and targeting improvement; 2) reflective-monitoring, assessing the body’s reaction to training and daily load; 3) coach-mediated, receiving insights through staff expertise; and 4) selective-disengagement, intentionally stepping back to protect confidence or avoid overload. These findings fill a gap left open by three related areas of research: SportsHCI, collegiate athletics, and personal data engagement. Each mode entails reasons, practices, and trade-offs. Student-athletes draw on different combinations of these modes as they respond to training demands, coaching oversight, and their own well-being. Our findings highlight how an evolving data ecology creates opportunities and pressures, requiring student-athletes to balance performance with protecting their state of mind.

Sharing high-quality research data specifically for reuse in future work helps the scientific community progress by enabling researchers to build upon existing work and explore new research questions without duplicating data collection efforts. Because current discussions about research artifacts in Computer Security focus on reproducibility and availability of source code, the reusability of data is unclear. We examine data sharing practices in Computer Security and Measurement to provide resources and recommendations for sharing reusable data. Our study covers five years (2019–2023) and seven conferences in Computer Security and Measurement, identifying 948 papers that create a dataset as one of their contributions. We analyze the 265 accessible datasets, evaluating their under-standability and level of reuse. Our findings reveal inconsistent practices in data sharing structure and documentation, causing some datasets to not be shared effectively. Additionally, reuse of datasets is low, especially in fields where the nature of the data does not lend itself to reuse. Based on our findings, we offer data-driven recommendations and resources for improving data sharing practices in our community. Furthermore, we encourage authors to be intentional about their data sharing goals and align their sharing strategies with those goals.

Continuous location sharing (CLS) applications are widely used for safety and social convenience. However, these applications have privacy concerns that can be used for control and harm. To understand user concerns, we performed the largest user study of CLS application usage performed to date, with 1500 of 3000 users indicating they use CLS applications and 896 of these users completing surveys. From survey responses, we conducted 23 interviews with participants who had uncomfortable experiences. With these interviews, we perform thematic analysis grounded by sociological frameworks of power dynamics and social exchange theory. We observe that CLS application users face discomfort related to three primary categories that build on each other: (1) overstepped boundaries, (2) continued discomfort, and (3) lifestyle-impacting behaviors. With this foundational understanding, we suggest features that aim to reduce relationship imbalances that CLS applications enable. Our resulting study demonstrates that CLS applications contribute to interpersonal discomfort, highlighting the need for design changes.

In 2022, the Anti-Phishing Working Group reported a 70% increase in SMS and voice phishing attacks. Hard data on SMS phishing is hard to come by, as are insights into how SMS phishers operate. Lack of visibility prevents law enforcement, regulators, providers, and researchers from understanding and confronting this growing problem. In this paper, we present the results of extracting phishing messages from over 200 million SMS messages posted over several years on 11 public SMS gateways on the web. From this dataset we identify 67,991 phishing messages, link them together into 35,128 campaigns based on sharing near-identical content, then identify related campaigns that share infrastructure to identify over 600 distinct SMS phishing operations. This expansive vantage point enables us to determine that SMS phishers use commodity cloud and web infrastructure in addition to self-hosted URL shorteners, their infrastructure is often visible days or weeks on certificate transparency logs earlier than their messages, and they reuse existing phishing kits from other phishing modalities. We are also the first to examine in-place network defenses and identify the public forums where abuse facilitators advertise openly. These methods and findings provide industry and researchers new directions to explore to combat the growing problem of SMS phishing.