Adversaries may exploit a range of vulnerabilities in Internet of Things (IoT) environments. These vulnerabilities are typically exploited to carry out attacks, such as denial-of-service (DoS) attacks, either against the IoT devices themselves, or using the devices to perform the attacks. These attacks are often successful due to the nature of the protocols used in the IoT. One popular protocol used for machine-to-machine IoT communications is the Message Queueing Telemetry Protocol (MQTT). Countermeasures for attacks against MQTT include testing defenses with existing datasets. However, there is a lack of real-world test datasets in this area. For this reason, this paper introduces a DoS/DDoS-MQTT-IoT dataset—that contains various DoS/DDoS attack scenarios using MQTT traffic—to help develop and test countermeasures against such attacks. To this end, a physical IoT testbed was constructed and a large volume of IoT data was generated that included standard MQTT traffic as well as 10 DoS scenarios. The usability of the dataset has been evaluated via machine learning.

Purpose Using technology to meet national security expectations and requirements is not new. Nations attempt to strike a balance between security and the (expressed or otherwise) privacy needs of citizens. Attacks (physical or cyber) on citizens shift the equilibrium point towards security. In contrast, civil liberties organisations act to preserve or increase privacy. The purpose of this paper is to explore Australian attitudes towards privacy and surveillance during the COVID-19 pandemic. In addition, this paper aims to discover what (if any) factors contribute to societal acceptance of privacy encroachment implicated by surveillance programs. Design/methodology/approach Data collection occurred during 2021 using a cross-sectional survey comprising a variety of self-assessment questions. In addition, anchoring vignettes were introduced as a means of contextualising complex concepts, i.e. privacy and security. Finally, latent class analysis (LCA) was used to identify homogenous patterns within the data, referred to as “classes” for the analysis of trust. Findings First, the survey revealed that citizens appear to be unconcerned about surveillance in public and private spaces (although this may be a temporary effect resulting from the pandemic). The potential for identification, however, does raise concerns. Second, LCA surfaced a specific group that were more likely to trust entities and showed less concern about surveillance in society. Finally, even this latter group displayed a “trust deficit” in specific organisations (private businesses and social media firms). Research limitations/practical implications The tension between security and privacy remains, even in a post-pandemic world; therefore, the authors consider that the results, whilst interesting, are preliminary. Notwithstanding this, the findings provide insight into Australian attitudes towards privacy and surveillance and, consequently, provide input into public policy. Originality/value This is the most recent survey of the Australian public concerning this issue. The analysis of the effect of the pandemic on attitudes provides further value.