20,161 research outputs found
The Viability and Potential Consequences of IoT-Based Ransomware
With the increased threat of ransomware and the substantial growth of the Internet of Things (IoT) market, there is significant motivation for attackers to carry out IoT-based ransomware campaigns. In this thesis, the viability of such malware is tested.
As part of this work, various techniques that could be used by ransomware developers to attack commercial IoT devices were explored. First, methods that attackers could use to communicate with the victim were examined, such that a ransom note was able to be reliably sent to a victim. Next, the viability of using "bricking" as a method of ransom was evaluated, such that devices could be remotely disabled unless the victim makes a payment to the attacker. Research was then performed to ascertain whether it was possible to remotely gain persistence on IoT devices, which would improve the efficacy of existing ransomware methods, and provide opportunities for more advanced ransomware to be created. Finally, after successfully identifying a number of persistence techniques, the viability of privacy-invasion based ransomware was analysed.
For each assessed technique, proofs of concept were developed. A range of devices -- with various intended purposes, such as routers, cameras and phones -- were used to test the viability of these proofs of concept. To test communication hijacking, devices' "channels of communication" -- such as web services and embedded screens -- were identified, then hijacked to display custom ransom notes. During the analysis of bricking-based ransomware, a working proof of concept was created, which was then able to remotely brick five IoT devices. After analysing the storage design of an assortment of IoT devices, six different persistence techniques were identified, which were then successfully tested on four devices, such that malicious filesystem modifications would be retained after the device was rebooted. When researching privacy-invasion based ransomware, several methods were created to extract information from data sources that can be commonly found on IoT devices, such as nearby WiFi signals, images from cameras, or audio from microphones. These were successfully implemented in a test environment such that ransomable data could be extracted, processed, and stored for later use to blackmail the victim.
Overall, IoT-based ransomware has not only been shown to be viable but also highly damaging to both IoT devices and their users. While the use of IoT-ransomware is still very uncommon "in the wild", the techniques demonstrated within this work highlight an urgent need to improve the security of IoT devices to avoid the risk of IoT-based ransomware causing havoc in our society. Finally, during the development of these proofs of concept, a number of potential countermeasures were identified, which can be used to limit the effectiveness of the attacking techniques discovered in this PhD research
Testing the nomological network for the Personal Engagement Model
The study of employee engagement has been a key focus of management for over three decades. The academic literature on engagement has generated multiple definitions but there are two primary models of engagement: the Personal Engagement Model of Kahn (1990), and the Work Engagement Model (WEM) of Schaufeli et al., (2002). While the former is cited by most authors as the seminal work on engagement, research has tended to focus on elements of the model and most theoretical work on engagement has predominantly used the WEM to consider the topic.
The purpose of this study was to test all the elements of the nomological network of the PEM to determine whether the complete model of personal engagement is viable. This was done using data from a large, complex public sector workforce. Survey questions were designed to test each element of the PEM and administered to a sample of the workforce (n = 3,103). The scales were tested and refined using confirmatory factor analysis and then the model was tested determine the structure of the nomological network. This was validated and the generalisability of the final model was tested across different work and organisational types.
The results showed that the PEM is viable but there were differences from what was originally proposed by Kahn (1990). Specifically, of the three psychological conditions deemed necessary for engagement to occur, meaningfulness, safety, and availability, only meaningfulness was found to contribute to employee engagement. The model demonstrated that employees experience meaningfulness through both the nature of the work that they do and the organisation within which they do their work. Finally, the findings were replicated across employees in different work types and different organisational types.
This thesis makes five contributions to the engagement paradigm. It advances engagement theory by testing the PEM and showing that it is an adequate representation of engagement. A model for testing the causal mechanism for engagement has been articulated, demonstrating that meaningfulness in work is a primary mechanism for engagement. The research has shown the key aspects of the workplace in which employees experience meaningfulness, the nature of the work that they do and the organisation within which they do it. It has demonstrated that this is consistent across organisations and the type of work. Finally, it has developed a reliable measure of the different elements of the PEM which will support future research in this area
Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective
This paper introduces a comprehensive, multi-stage machine learning
methodology that effectively integrates information systems and artificial
intelligence to enhance decision-making processes within the domain of
operations research. The proposed framework adeptly addresses common
limitations of existing solutions, such as the neglect of data-driven
estimation for vital production parameters, exclusive generation of point
forecasts without considering model uncertainty, and lacking explanations
regarding the sources of such uncertainty. Our approach employs Quantile
Regression Forests for generating interval predictions, alongside both local
and global variants of SHapley Additive Explanations for the examined
predictive process monitoring problem. The practical applicability of the
proposed methodology is substantiated through a real-world production planning
case study, emphasizing the potential of prescriptive analytics in refining
decision-making procedures. This paper accentuates the imperative of addressing
these challenges to fully harness the extensive and rich data resources
accessible for well-informed decision-making
Towards Evaluating Explanations of Vision Transformers for Medical Imaging
As deep learning models increasingly find applications in critical domains
such as medical imaging, the need for transparent and trustworthy
decision-making becomes paramount. Many explainability methods provide insights
into how these models make predictions by attributing importance to input
features. As Vision Transformer (ViT) becomes a promising alternative to
convolutional neural networks for image classification, its interpretability
remains an open research question. This paper investigates the performance of
various interpretation methods on a ViT applied to classify chest X-ray images.
We introduce the notion of evaluating faithfulness, sensitivity, and complexity
of ViT explanations. The obtained results indicate that Layerwise relevance
propagation for transformers outperforms Local interpretable model-agnostic
explanations and Attention visualization, providing a more accurate and
reliable representation of what a ViT has actually learned. Our findings
provide insights into the applicability of ViT explanations in medical imaging
and highlight the importance of using appropriate evaluation criteria for
comparing them.Comment: Accepted by XAI4CV Workshop at CVPR 202
A Descriptive Qualitative Study Exploring Middle-School Teachers’ Perceptions of Professional Development on Technology Integration
Today’s teachers are being encouraged to incorporate technology into their classrooms. Technology integration became a worldwide focus for schools after remote learning was necessary to continue instruction due to the COVID-19 pandemic. Additionally, research shows that technology-infused lessons improve student achievement and increase student engagement. Despite efforts to support teachers throughout the technology integration process, concerns have developed. Preparing highly qualified teachers ready to incorporate technology into their teaching repertoire has developed additional stress factors. In this descriptive qualitative study, the researcher wanted to address the problem of teacher attrition, possibly related to stress factors associated with technology integration. The purpose of this qualitative descriptive study was to explore teachers’ perceptions of professional development opportunities that possibly improve the technology integration process. Additionally, the researcher wanted to identify stress factors associated with technology adoption and how professional development may help to reduce stress factors associated with technology integration in one middle school in New York. The researcher chose a qualitative descriptive study using Vygotsky’s social constructivist theory and Bandura’s social learning theory on self-efficacy as the theoretical framework. The researcher included an exposition of the literature sources, synthesized the research findings, and provided recommendations for practice and future research. The data collection process consisted of semistructured open-ended questions that were developed with the support of a panel of experts. There were 10 participants chosen using a snowball sampling strategy. This study’s findings were that professional development should be hands-on, continuous, and targeted to increase teachers’ personal level of engagement. Also, creating opportunities for colleague support systems reduced stress factors associated with technology integration. These peer support systems reduced the time required to research the most effective resources, digital tools, and applications as participants shared the resources with one another. Recommendations for practice included providing adequate professional development, offering appropriate infrastructure, and hands-on, targeted, continuous training for teachers to feel more comfortable developing technology-infused lessons. Recommendations for research include providing additional insight into teachers’ perceived benefits and motivation for technology integration and how stress factors associated with the technology adoption process possibly increase teacher attrition
Explaining the psychological experiences of nurses during the first peak COVID-19 pandemic
Introduction: The unexpected spread of COVID-19 with high risk of transmission, fear and anxiety, and a load of negative emotions followed for nurses. It is necessary to assess the psychological experiences of nurses during the first peak COVID-19 pandemic.
Materials and Methods: In this qualitative study, with the approach of conventional content analysis approach, the participants were selected through proposed-based sampling and snowball from the COVID-19 centers of Guilan province in March 2020. The number of 20 participants with various demographic characteristics (Gender, age ...) entered the study. The tools used were in-depth and semi-structured interviews.
Results: Most of the participants were women, married and nurses. Six categories were obtained: not perception, worries, and pretending, horrible observations, pre-psychological symptoms and psychological symptoms.
Conclusion: Psychological experiences of nurses in COVID-19 center in Guilan were expressed in a range of not perceptions and worry until the appearance of numerous pre and psychological symptoms. The psychological needs of this group must be considered at all stages of the crisis. Psychological support by mental health workers should be considered in line with the development of the crisis to reduce the stress on nurses
A citizen science approach to the characterisation and modelling of urban pluvial flooding
Urban pluvial flooding (UPF), a growing challenge across cities worldwide that is expected to worsen
due to climate change and urbanisation, requires comprehensive response strategies. However, the
characterisation and simulation of UPF is more complex than traditional catchment hydrological modelling because
UPF is driven by a complex set of interconnected factors and modelling constraints. Different integrated approaches
have attempted to address UPF by coupling humans and environmental systems and reflecting on the possible
outcomes from the interactions among varied disciplines. Nonetheless, it is argued that current integrated
approaches are insufficient. To further improve the characterisation and modelling of UPF, this study advances a
citizen science approach that integrates local knowledge with the understanding and interpretation of UPF. The
proposed framework provides an avenue to couple quantitative and qualitative community-based observations
with traditional sources of hydro-information. This approach allows researchers and practitioners to fill spatial and
temporal data gaps in urban catchments and hydrologic/hydrodynamic models, thus yielding a more accurate
characterisation of local catchment response and improving rainfall-runoff modelling of UPF. The results of applying
this framework indicate how community-based practices provide a bi-directional learning context between experts
and residents, which can contribute to resilience building by providing UPF knowledge necessary for risk reduction
and response to extreme flooding events
Considerations Perceived by Coaches as Specific to Coaching Elite Women’s Soccer Teams
This study investigated challenges perceived by coaches when working with elite women’s soccer teams. Six men and four women coaches with experience in the first Norwegian League or Norwegian national team participated. Semi-structured interviews were carried out, and the data was analyzed using thematic interpretational analysis. Participants identified professionalism, early-career termination, mental characteristics, intrateam communication, romantic relationships, access to the locker rooms (men only), and team selection (women only) as the specific challenges they face when coaching these teams. The findings are discussed in relation to ensuring that good performance and development are achieved when coaching elite women’s soccer teams and helping future coaches optimize their coaching techniques when working with elite women players
A Phenomenological Study of How Active Engagement in Black Greek Letter Sororities Influences Christian Members\u27 Spiritual Growth
This phenomenological study explored how being part of a Black Greek Letter. Organization (BGLO) sorority impacts the spiritual growth of its Christian members. One of the issues explored was the influence relationships within these sororities have on members striving to be like Christ. There is a dichotomy of perspectives regarding Black Greek Letter Organizations (BGLOs). They have a significant role in the Black community as organizations that foster leadership, philanthropy, and sisterhood and promote education. They are admired on and off college campuses and in the broader community in graduate chapters. The objective of phenomenology is to describe phenomena of spiritual growth among Christian sorority members from the life experiences of those who live them; that premise guided the interviews conducted for this study. The results found that active engagement in a BGLO sorority positively impacts its members\u27 spiritual growth. From the emotional stories of sisterhood, service, and devotion to prayer, their experiences evidenced strengthened walks of faith. This study contrasts the Anti-BGLO narrative as a testament to these organizations\u27 legacy and practices deeply grounded in the church
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