The Domain Name System (DNS) translates human-readable domain names into machine-readable IP addresses. This critical internet infrastructure faces increasing exploitation through various malicious activities collectively known as DNS abuse. While DNS abuse has been extensively researched globally, the unique patterns and vulnerabilities within the Australian domain space remain understudied. This paper provides a comprehensive empirical analysis of DNS abuse within Australian domain names. Our thorough data collection and analysis allow us to characterize the specific nature of abuse trends within the Australian domain space. We document how malicious actors strategically employ methods to evade detection systems, and highlight the concentration of abuse among specific domain registrations. These research findings provide stakeholders with actionable, data-driven insights, emphasizing the necessity of industry-specific defensive measures and tailored state-level threat mitigation strategies. We have laid the foundation for building a more refined, risk-based Australian digital infrastructure security system.

Limited training capacity has contributed to a critical shortage of licensed commercial pilots.Adaptive educational technologies and simulators could alleviate current training bottlenecks if these technologies could assess trainee performance and provide appropriate feedback.Agents can be used to assess trainee performance, but there is insufficient guidance on how to provide concurrent feedback in simulation-based learning environments.So, we designed 4 feedback conditions that provide varying degrees of elaboration and used a within-subject study (𝑛 = 20) to compare feedback approaches.Trainee performance was best when they received highly-elaborative feedback that modeled expert behaviour.Variability in participant performance and preferences indicates a need to adapt the feedback type to individual learners and provides insight into the use of concurrent feedback in simulation-based learning environments.Specifically, learners appreciated the expert model because it facilitated a sense of control which was associated with lower negative affect and lower extraneous cognitive load.

Educational technologies have been argued to enhance specific aspects of affect, such as motivation, and through that learner experiences and outcomes. Until recently, affect has been considered separately from cognition. In this study, we investigated how learner affect (valence and activation) was tied to learner cognitive load and behaviours during game-based literacy activities. We employed experience sampling as part of a lab-based case study where 35 English language learners used an adaptive educational game. The results indicated that both positive and negative affect predicted learner cognitive load, with negative affect predicting extraneous (unnecessary) load. These results and the newly identified interaction patterns that accompanied learner affect and cognitive-load trajectories provide insight into the role of affect during learning. They show a need for considering affect when studying cognitive load and have implications for how systems should adapt to learners.

A large part of health education involves acquiring operational skills that require continued cooperation from the sense of sight. Traditional skill-training systems heavily rely on post-task evaluation and cannot automatically identify the tacit knowledge (e.g., visual attention allocation) that is used to support the decision-making and tool manipulation process. Recent research has started addressing this issue by identifying learner behaviours to understand learner needs and respond with personalized real-time support. To enable this type of adaptivity when training people in how to give injections, we conducted a study to investigate user's visual attention. We analyzed the eye-tracking data of 8 skilled medical practitioners and 10 student nurses from when they were performing an injection task on a simulated abdominal pad. Differences in the detected visual attention and eye-scan patterns across expertise levels create an opportunity for using overlay models or other diagnosis approaches to provide adaptive support to nurse trainees.

We present Trip Together, a remote pair sightseeing system supporting gestural communication between a user remaining indoor and a remote partner going outside. With the integration of Head-mounted Display and Depth Camera, we allow the local user to perform a gestural interaction with the remote user on top of the remote scene while each user is provided an independent free viewpoint. Using Trip Together, two side of users could get a feeling that they are truly walking outdoor together side by side for a trip. We have received positive feedback from a preliminary user study.