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Inferring Attacks on a Distributed Honeyfarm Using Adversary Emulation and Centralized Threat Detection
Full text linkSecuring industrial control systems (ICSs) is difficult. This research aims to improve ICS security with data collected by a distributed honeyfarm (a network of honeypots). We deployed cloud-based honeypots in Europe and North America to monitor and analyze real-world attacks on simulated power grids and ICS devices. Our honeyfarm included a centralized enterprise-grade Security Information and Event Management (SIEM) system for real-time threat detection. We used MITRE Caldera adversary emulation, MITRE ATT&CK, system logs, and network-intrusion alerts to create SIEM queries. This approach distinguishes our honeyfarm from other research. We observed exploits of network protocols and legitimate services, remote code execution, brute-force credential cracking, denial of service, and botnet activity. RDP activity indicated possible human involvement. Our results showed that a SIEM system trained with adversary-emulation results and intrusion-detection alerts collected data on 16 times more suspicious intruders and improved detection of their threats, enabling better defenses
From Fear to Opportunity: Unlocking the Potential of Bidirectional Feedback in Higher Education
Full text linkBidirectional feedback has the potential to significantly benefit students by enhancing learning success and goal achievement, while also enabling teachers to better address students’ needs and improve learning material. However, current feedback practices face several challenges, including students’ difficulty in formulating clear and actionable feedback, the effort required for both students and teachers to engage in meaningful feedback dialogues, and the burden on teachers to manage and respond to a high amount of feedback across diverse learning materials. These challenges often lead to concerns about teacher overload, which can hinder the adoption of bidirectional feedback practices. We leverage an existing bidirectional feedback tool, including its process model, computational design, and Moodle implementation for self-assessment tasks. Using data from three consecutive semesters in a B.Sc. Computer Science distance learning course, we show that the tool does not increase feedback overload for teachers. Instead, it enables a balanced flow of constructive and positive feedback, which teachers found actionable and useful for improving assignments and supporting learning. By comparing the three semesters, we demonstrate that the tool successfully mitigates concerns about feedback overload while maintaining the benefits of bidirectional feedback. This finding highlights the usability and sustainability of the approach, offering a practical solution for integrating bidirectional feedback into higher education without overwhelming teachers
The Color of Engagement: How Visual Hue, Hedonic Cues, and Audio Arousal Shape Fan Attention in Short-Form Sports Videos
Full text linkWe analyze 100 fan-generated TikTok videos from the 2025 NCAA Men’s Basketball Tournament to examine how visual hue, branding, hedonic cues, and audio arousal relate to engagement. Using computer vision and audio signal processing, we test theory-driven hypotheses within a model framework. Results show directional evidence for a U-shaped association between hue and engagement; this pattern appears stronger when hedonic cues are present and weaker under high audio arousal, consistent with accounts of affective amplification and multimodal overload. Given the small sample and measurement limits, we treat non-significant effects as exploratory. We contribute an ecologically grounded approach for studying multimodal attention in short-form sports media and offer practical guidance: design for sensory balance (color intensity with moderated audio) rather than saturation. Future work should scale data, incorporate saliency-weighted and temporal visual features, and examine algorithmic mediation
A Meta-Analytic Review of Sanctions in Organizational Cybersecurity
Full text linkSanctions are central to regulatory strategies designed to deter violations of organizational cybersecurity policies. Yet, their effectiveness in shaping cybersecurity behaviour, particularly among non-malicious insiders, remains unclear, with empirical findings showing considerable inconsistency. This meta-analysis synthesizes evidence from 51 studies to examine the differential impact of sanctions on two key outcomes: compliance intentions and violation intentions. The results reveal that sanction certainty significantly increases compliance intentions but has no significant effect on violation intentions, challenging the assumption of symmetrical deterrence. Additionally, sanction celerity moderates the effects of both detection certainty and sanction severity on compliance, while sample size and geographic factors moderate the relationship between sanction severity and violation intentions. These findings offer important refinements to sanctions-based deterrence models and suggest directions for future research
Intersection of TikTok/Douyin and Dementia: A Scoping Review of Research to Date (2016-May 2025)
Full text linkShort-form video platforms like TikTok play a special cultural role for this decade, enabling research in a range of fields, including health and information sciences. With 55 million Alzheimer's and other dementia cases worldwide, research has started to include TikTok and Douyin as a tool, a site, or a context for understanding and improving dementia-related lived experiences. This review of 15 articles is the first to assess the scope of TikTok/Douyin research (2016-May 2025) on dementia since the apps were launched, identifying the role of TikTok/Douyin in dementia research, shedding light on where the current science is and in which directions future research can better leverage TikTok/Douyin. Implications of findings for dementia care practice and the design of information technology in healthcare are also discussed
Will They Be More Honest With an (External) Proctor? Evaluating UFC Match Performance Before and After the Adoption of the USADA Doping Program
Full text linkOver the eight years from 2015 to 2023, the Ultimate Fighting Championship (UFC) partnered with the United States Anti-Doping Agency (USADA) to institute comprehensive external oversight of doping controls. This study investigates the effects of transitioning from internally administered anti-doping protocols to exclusive external governance by comparing UFC performance metrics before and during the USADA partnership. Using a Difference-in-Differences (DiD) approach with data from 2012 to 2018, we find that match duration significantly increased, while the likelihood of extreme outcomes, knockouts (KO), technical knockouts (TKO), and submissions, decreased during the USADA period. These results suggest that performance-enhancing drugs (PEDs) could be more prevalent before USADA oversight and declined once stricter testing was introduced. The findings imply that UFC’s move away from USADA could lead to increased PED use among fighters
Navigating Generative AI Disruptions: A Process Model of Occupational Resilience
Full text linkGenerative Artificial Intelligence (GenAI) is transforming knowledge workers by introducing automation capabilities that challenge traditional notions of expertise, creativity, and problem-solving. While GenAI offers new opportunities for productivity and innovation, it also disrupts professional identities, raising concerns about job displacement, occupational shifts, and ethical dilemmas. This study examines how knowledge workers (KWers) develop occupational resilience when faced with GenAI transformations. Building on prior literature on resilience, we propose that occupational resilience is critical for sustaining professional relevance and well-being in the GenAI era. Using a grounded theory approach, we present early qualitative insights from thirteen interviews to propose a process model of GenAI occupational resilience. By addressing these challenges, this study contributes to a deeper understanding of GenAI’s impact on KWers and offers insights for developing adaptation strategies
Efficient Investments in Community Choice Aggregation through Stable Uniform Price Cost Sharing
Full text linkIncreasingly ubiquitous solar panels in residential buildings and the end of net metering programs make energy communities increasingly attractive for prosumers to reduce their electricity costs. In this context, cooperative game theory models have been proposed to find a mechanism to distribute collective cost savings among community members. We address here a shortcoming in a recently proposed mechanism to share savings through uniform price allocations stemming from shadow prices of a linear program. We show that in cases where existing local rooftop generation is sufficiently high, that mechanism may incentivize inefficient investments by under-compensated participants. We propose a modified mechanism in which investment decisions are part of the optimization problem and show that the desirable properties of game-theoretic stability and computational tractability are maintained, while incentivizing only efficient investments. We show theoretical results, illustrate the proposed model via examples and discuss remaining challenges for the approach