Cybersecurity challenges in blockchain technology : a scoping review

Blockchain technology (BCT) is an emerging technology. Cybersecurity challenges in BCT are being explored to add greater value to business processes and reshape business operations. This scoping review paper was aimed at exploring the current literature's scope and categorizing various types of cybersecurity challenges in BCT. Databases such as Elsevier, ResearchGate, IEEE, ScienceDirect, and ABI/INFORM Collection (ProQuest) were searched using a combination of terms, and after rigorous screening, 51 research studies were found relevant. Data coding was performed following a framework proposed for scoping review. After careful analysis, thirty different types of cybersecurity challenges in BCT were categorized into six standardized classes. Our results show that most of the studies disclose cybersecurity challenges in BCT generally without pointing to any specific industry sector, and to a very little extent, few papers reveal cybersecurity challenges in BCT related to specific industry sectors. Also, prior studies barely investigated the strategies to minimize cybersecurity challenges in BCT. Based on gap identification, future research avenues were proposed for scholars

Educational anomaly analytics : features, methods, and challenges

Anomalies in education affect the personal careers of students and universities' retention rates. Understanding the laws behind educational anomalies promotes the development of individual students and improves the overall quality of education. However, the inaccessibility of educational data hinders the development of the field. Previous research in this field used questionnaires, which are time- and cost-consuming and hardly applicable to large-scale student cohorts. With the popularity of educational management systems and the rise of online education during the prevalence of COVID-19, a large amount of educational data is available online and offline, providing an unprecedented opportunity to explore educational anomalies from a data-driven perspective. As an emerging field, educational anomaly analytics rapidly attracts scholars from a variety of fields, including education, psychology, sociology, and computer science. This paper intends to provide a comprehensive review of data-driven analytics of educational anomalies from a methodological standpoint. We focus on the following five types of research that received the most attention: course failure prediction, dropout prediction, mental health problems detection, prediction of difficulty in graduation, and prediction of difficulty in employment. Then, we discuss the challenges of current related research. This study aims to provide references for educational policymaking while promoting the development of educational anomaly analytics as a growing field. Copyright © 2022 Guo, Bai, Tian, Firmin and Xia

Multimodal educational data fusion for students' mental health detection

Mental health issues can lead to serious consequences like depression, self-mutilation, and worse, especially for university students who are not physically and mentally mature. Not all students with poor mental health are aware of their situation and actively seek help. Proactive detection of mental problems is a critical step in addressing this issue. However, accurate detections are hard to achieve due to the inherent complexity and heterogeneity of unstructured multi-modal data generated by campus life. Against this background, we propose a detection framework for detecting students' mental health, named CASTLE (educational data fusion for mental health detection). Three parts are involved in this framework. First, we utilize representation learning to fuse data on social life, academic performance, and physical appearance. An algorithm, named MOON (multi-view social network embedding), is proposed to represent students' social life in a comprehensive way by fusing students' heterogeneous social relations effectively. Second, a synthetic minority oversampling technique algorithm (SMOTE) is applied to the label imbalance issue. Finally, a DNN (deep neural network) model is utilized for the final detection. The extensive results demonstrate the promising performance of the proposed methods in comparison to an extensive range of state-of-the-art baselines. © 2013 IEEE

Informing app design to reduce self-management challenges identified for chronic disease

Self-managing chronic diseases is challenging for patients and involves handling a range of long-term treatments. Patients have many responsibilities to manage. Feeling overwhelmed by this information can lead to a sense of hopelessness and depression. Mobile apps can be beneficial support for chronically ill patients to selfmanage their condition. Many apps are available for various purposes, such as fitness and daily wellbeing, but none are customised for chronically ill patients who need to manage their disease daily. The purpose of this paper is to propose an approach to identify the critical challenges faced by patients when self-managing their chronic illness. These challenges will inform the design of a customised mobile app that is user friendly and will assist patients in managing their disease efficiently and effectively. A qualitative interpretive approach analysed through the theoretical lens of the theory of planned behaviour (TPB) is the proposed methodology for this project. Interpretivism is about understanding people in their natural world. The social world of people with chronic illnesses is lonely and isolating. The TPB connects a persons attitudes and behaviour. Understanding chronically ill patients feelings of isolation and helplessness through data gathered by semi-structured open-ended interviews will enable a thematic analysis of the critical challenges chronically ill patients face. This paper provides a unique approach for identifying and analysing critical issues that the chronically ill face from a patient viewpoint. These issues will be used to customise the design of an app for self-management purposes. © 2022 Association for Computing Machinery. All rights reserved

Enhancing self-efficacy for fluid management in chronic kidney disease with fitbit and flex

Chronic kidney disease patients are required to restrict their fluid intake quite severely. Compliance is particularly challenging for many patients but failing to comply can lead to life-threatening consequences. There is some evidence that behaviour change programs based on education are effective, however a program known as Flex that is based on encouraging patients to be more adaptable and adhere less rigidly to a range of habits of daily living has not been evaluated. A core feature of the Flex program is the generation of text messages to remind patients to perform previously agreed habit changes (known as Do's) based on the analysis of Fitbit data. This study aims to apply a constructivist, qualitative methodology with a group of chronic kidney disease patients to assess the extent to which the Flex program has a positive impact on self-efficacy and ultimately on fluid management. © 2022 ACM

An interpretive study of stakeholders privacy issues in blockchain : a healthcare context

Ever-growing and rapidly changing healthcare information systems (HIS) encourage many new technologies to integrate with it to enrich the treatment and facilitate patients. Blockchain, a decentralised digital ledger, is legitimately disrupting traditional HIS due to its characteristics such as immutability, interoperability, decentralise, and security. Blockchain' applications in healthcare industries are attracting investors and organisations to develop platforms for future. However, security and privacy concerns hinder blockchain adoption in the health sector. Therefore, there is a need to develop deeper understandings about these issues and require strategies to address these issues so that the desired values can be obtained. Besides, privacy could mean different to different people such as patients, doctors, and admin staff. Therefore, there is a need to explore it from various stakeholder perspectives too. Using interpretive qualitative research approach, this research-in-progress will extend the body of knowledge by scrutinising the stakeholders' perception of privacy concerns and its relationship in blockchain based HIS. The findings of this study will contribute to address privacy issues emerged from the research and help to eliminate them before implementing blockchain. This paper supplies an appropriate research approach for multidimensional research in healthcare. In addition, this research-in progress will formulate a framework which provide awareness to stakeholders about privacy issues when they use blockchain based HIS in future. © 2022 ACM

Countermeasure Strategies to Address Cybersecurity Challenges Amidst Major Crises in the Higher Education and Research Sector: An Organisational Learning Perspective

Purpose: The purpose of this research paper was to analyse the counterstrategies to mitigate cybersecurity challenges using organisational learning loops amidst major crises in the Higher Education and Research Sector (HERS). The authors proposed the learning loop framework revealing several counterstrategies to mitigate cybersecurity issues in HERS. The counterstrategies are explored, and their implications for research and practice are discussed. Methodology: The qualitative methodology was adopted, and semi-structured interviews with cybersecurity experts and top managers were conducted. Results: This exploratory paper proposed the learning loop framework revealing introducing new policies and procedures, changing existing systems, partnership with other companies, integrating new software, improving employee learning, enhancing security, and monitoring and evaluating security measures as significant counterstrategies to ensure the cyber-safe working environment in HERS. These counterstrategies will help to tackle cybersecurity in HERS, not only during the current major crisis but also in the future. Implications: The outcomes provide insightful implications for both theory and practice. This study proposes a learning framework that prioritises counterstrategies to mitigate cybersecurity challenges in HERS amidst a major crisis. The proposed model can help HERS be more efficient in mitigating cybersecurity issues in future crises. The counterstrategies can also be tested, adopted, and implemented by practitioners working in other sectors to mitigate cybersecurity issues during and after major crises. Future research can focus on addressing the shortcomings and limitations of the proposed learning framework adopted by HERS

A framework for data privacy and security accountability in data breach communications

Organisations need to take steps to protect the privacy and security of the personal information they hold. However, when data is breached, how do individuals know whether the organisation took reasonable steps to protect their data? When breached organisations notify affected individuals, this communication is likely to be one of the few windows into the incident from the outside and can become an important artefact for research. This desktop study aimed to consider the extent to which publicly available Australian data breach communications reflect data privacy and security best practices. This paper presents a brief review of literature and government guidance on data security and privacy best practices, along with the results of a qualitative content analysis of 33 publicly available Australian data breach communications. This analysis illustrated that there was little reflection of data privacy and security practices. Literature, government guidance and the content analysis were used to inform and develop a new voluntary framework for organisations. This consists of a series of evaluation questions divided into two broad categories: responsible data management and responsible portrayal of the breach. The framework has the potential to help organisations plan the inclusion of data privacy and security management aspects in their data breach communications. This could assist organisations to address their legal and ethical responsibility to account for their actions in managing privacy and security of the personal data they hold. © 202

Decoding Employee ambidexterity: Understanding drivers, constraints, and performance implications for thriving in the evolving work landscapes - A scoping review

Employee ambidexterity (EA) is becoming increasingly recognised as a significant factor in enhancing individual and organisational performance across diverse industries. Ambidexterity refers to the capacity to exploit and explore organisational resources simultaneously. Scholars from diverse industry sectors have been motivated to delve deeper into the topic of EA due to its growing popularity. The objective of conducting a scoping review was to scrutinise the existing literature and identify the key drivers and constraints that impact EA to thrive in the changing work landscape. The insights gained from this review can assist decision-makers in formulating effective strategies to cultivate the ambidexterity skills of their workforce and achieve desirable outcomes. This review adheres to the PRISMA-ScR protocol. Articles were obtained from databases including Scopus, Web of Science, and EBSCOhost (Academic Search Complete, Business Source Complete). The body of literature concerning EA is in its nascent stage. 23 articles assessing EA's performance outcomes were identified using targeted search terms and thorough screening. After conducting a thorough thematic analysis using the iterative categorisation (IC) technique, tailored for scoping a review, we successfully identified twenty-nine factors contributing to the enhancement of EA, meticulously organised into five distinct categories: organisational factors, social connectedness, employee behaviour, employee personality, and work environment related factors. Similarly, we discovered four factors that impede EA: functional tenure, team identification, bounded discretion, and conscientiousness. Our findings underscore the profound impact of employee ambidexterity on distinct types of performance. Among the sixteen types of performance reported to be enhanced by EA, ten are linked to individual performance, while six are tied to organisational performance. Notably, our analysis revealed that nearly all studies have relied on cross-sectional research methods except for one. However, we advocate for the exploration of longitudinal studies as they hold the promise of offering a more comprehensive understanding of EA. The paper presents valuable insights into how to cultivate ambidextrous capabilities in the workforce for unparalleled success in today's rapidly evolving work environment. Additionally, it identifies several intriguing avenues for future research that could further elucidate and bridge existing knowledge gaps