Think twice before you click! : exploring the role of human factors in cybersecurity and privacy within healthcare organizations

The urgent need to protect sensitive patient data and preserve the integrity of healthcare services has propelled the exploration of cybersecurity and privacy within healthcare organizations [1]. Recognizing that advanced technology and robust security measures alone are insufficient [2], our research focuses on the often-overlooked human element that significantly influences the efficacy of these safeguards. Our motivation stems from the realization that individual behaviors, decision-making processes, and organizational culture can be both the weakest link and the most potent tool in achieving a secure environment. Understanding these human dimensions is paramount as even the most sophisticated protocols can be undone by a single lapse in judgment. This research explores the impact of human behavior on cybersecurity and privacy within healthcare organizations and presents a new methodological approach for measuring and raising awareness among healthcare employees. Understanding the human influence in cybersecurity and privacy is critical for mitigating risks and strengthening overall security posture. Moreover, the thesis aims to place emphasis on the human aspects focusing more on the often-overlooked factors that can shape the effectiveness of cybersecurity and privacy measures within healthcare organizations. We have highlighted factors such as employee awareness, knowledge, and behavior that play a pivotal role in preventing security incidents and data breaches [1]. By focusing on how social engineering attacks exploit human vulnerabilities, we underline the necessity to address these human influenced aspects. The existing literature highlights the crucial role that human factors and awareness training play in strengthening cyber resilience, especially within the healthcare sector [1]. Developing well-customized training programs, along with fostering a robust organizational culture, is vital for encouraging a secure and protected digital healthcare setting [3]. Building on the recognized significance of human influence in cybersecurity within healthcare organizations, a systematic literature review became indispensable. The existing body of research might not have fully captured all ways in which human factors, such as psychology, behavior, and organizational culture, intertwined with technological aspects. A systematic literature review served as a robust foundation to collate, analyze, and synthesize existing knowledge, and to identify gaps where further research was needed. In complement to our systematic literature review and investigation of human factors, our research introduced a new methodological approach through a concept study based on an exploratory survey [4]. Recognizing the need to uncover intricate human behavior and psychology in the context of cybersecurity, we designed this survey to probe the multifaceted dimensions of cybersecurity awareness. The exploratory nature of the survey allowed us to explore cognitive, emotional, and behavioral aspects, capturing information that is often overlooked in conventional analyses. By employing this tailored survey, we were able to collect insights that provided a more textured understanding of how individuals within healthcare organizations perceive and engage with cybersecurity measures

VISTA:an inclusive insider threat taxonomy, with mitigation strategies

Insiders have the potential to do a great deal of damage, given their legitimate access to organisational assets and the trust they enjoy. Organisations can only mitigate insider threats if they understand what the different kinds of insider threats are, and what tailored measures can be used to mitigate the threat posed by each of them. Here, we derive VISTA (inclusiVe InSider Threat tAxonomy) based on an extensive literature review and a survey with C-suite executives to ensure that the VISTA taxonomy is not only scientifically grounded, but also meets the needs of organisations and their executives. To this end, we map each VISTA category of insider threat to tailored mitigations that can be deployed to reduce the threat

A unified classification model to insider threats to information security

Prior work on insider threat classification has adopted a range of definitions, constructs, and terminology, making it challenging to compare studies. We address this issue by introducing a unified insider threat classification model built through a comprehensive and systematic review of prior work. An insider threat can be challenging to predict, as insiders may utilise motivation, creativity, and ingenuity. Understanding the different types of threats to information security (and cybersecurity) is crucial as it helps organisations develop the right preventive strategies. This paper presents a thematic analysis of the literature on the types of insider threats to cybersecurity to provide cohesive definitions and consistent terminology of insider threats. We demonstrate that the insider threat exists on a continuum of accidental, negligent, mischievous, and malicious behaviour. The proposed insider threat classification can help organisations to identify, implement, and contribute towards improving their cybersecurity strategies

The enemy has passed through the gate: insider threats, the dark triad, and the challenges around security

Purpose – The purpose of this paper is to highlight the potential role that the so-called “toxic triangle” (Padilla et al., 2007) can play in undermining the processes around effectiveness. It is the interaction between leaders, organisational members, and the environmental context in which those interactions occur that has the potential to generate dysfunctional behaviours and processes. The paper seeks to set out a set of issues that would seem to be worthy of further consideration within the Journal and which deal with the relationships between organisational effectiveness and the threats from insiders.<p></p> Design/methodology/approach – The paper adopts a systems approach to the threats from insiders and the manner in which it impacts on organisation effectiveness. The ultimate goal of the paper is to stimulate further debate and discussion around the issues.<p></p> Findings – The paper adds to the discussions around effectiveness by highlighting how senior managers can create the conditions in which failure can occur through the erosion of controls, poor decision making, and the creation of a culture that has the potential to generate failure. Within this setting, insiders can serve to trigger a series of failures by their actions and for which the controls in place are either ineffective or have been by-passed as a result of insider knowledge.<p></p> Research limitations/implications – The issues raised in this paper need to be tested empirically as a means of providing a clear evidence base in support of their relationships with the generation of organisational ineffectiveness.<p></p> Practical implications – The paper aims to raise awareness and stimulate thinking by practising managers around the role that the “toxic triangle” of issues can play in creating the conditions by which organisations can incubate the potential for crisis.<p></p> Originality/value – The paper seeks to bring together a disparate body of published work within the context of “organisational effectiveness” and sets out a series of dark characteristics that organisations need to consider if they are to avoid failure. The paper argues the case that effectiveness can be a fragile construct and that the mechanisms that generate failure also need to be actively considered when discussing what effectiveness means in practice.<p></p&gt

Information Systems Security Countermeasures: An Assessment of Older Workers in Indonesian Small and Medium-Sized Businesses

Information Systems (IS) misuse can result in cyberattacks such as denial-of-service, phishing, malware, and business email compromise. The study of factors that contribute to the misuse of IS resources is well-documented and empirical research has supported the value of approaches that can be used to deter IS misuse among employees; however, age and cultural nuances exist. Research focusing on older workers and how they can help to deter IS misuse among employees and support cybersecurity countermeasures within developing countries is in its nascent stages. The goal of this study was two-fold. The first goal was to assess what older workers within Indonesian Small to Medium-sized Businesses (SMBs) do to acquire, apply, and share information security countermeasures aimed at mitigating cyberattacks. The second goal was to assess if and how younger workers share information security countermeasures with their older colleagues. Using a qualitative case study approach, semi-structured interviews were conducted with five dyads of older (50-55 years) and younger (25-45 years) workers from five SMBs in Jakarta, Indonesia. A thematic analysis approach was used to analyze the interview data, where each dyad represented a unit of analysis. The data were organized into three main themes including 1) Indonesian government IS policy and oversight, which included one topic (stronger government IS oversight needed); 2) SMB IS practices, which included three topics (SMB management issues, SMB budget constraints, SMB diligent IS practices, and IS insider threat); and 3) SMB worker IS practices, which included three topics (younger worker job performance, IS worker compliance issues, older worker IS practices) and five sub-topics under older worker IS practices (older worker diligent in IS, older worker IS challenged, older worker riskier IS practices, older worker more IS dependent, and older worker more forgetful on IS practices). Results indicated that older and younger workers at Indonesian SMBs acquire, apply, and share information security countermeasures in a similar manner: through IS information dissemination from the SMB and through communication from co-workers. Also, while younger workers share IS countermeasures freely with their older co-workers, some have negative perceptions that older co-workers are slower and less proficient in IS. Overall, participants reported positive and cohesive teamwork between older and younger workers at SMBs through strong IS collaboration and transparent information sharing. The contribution of this research is that it provides valuable empirical data on older worker behavior and social dynamics in Indonesian organizations. This was a context-specific study aimed at better understanding the situationalities of older workers within organizations in the developing country of Indonesia and how knowledge is shared within the organization. This assessment of cybersecurity knowledge acquisition, skill implementation, and knowledge sharing contributes to the development of organization-wide cybersecurity practices that can be used to strengthen Indonesian SMBs and other organizations in developing countries. This study also provides a blueprint for researchers to replicate and extend this line of inquiry. Finally, the results could shed light on how older workers can be a productive part of the solution to information security issues in the workplace

Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future

Given the exponential expansion of the internet, the possibilities of security attacks and cybercrimes have increased accordingly. However, poorly implemented security mechanisms in the Internet of Things (IoT) devices make them susceptible to cyberattacks, which can directly affect users. IoT forensics is thus needed for investigating and mitigating such attacks. While many works have examined IoT applications and challenges, only a few have focused on both the forensic and security issues in IoT. Therefore, this paper reviews forensic and security issues associated with IoT in different fields. Future prospects and challenges in IoT research and development are also highlighted. As demonstrated in the literature, most IoT devices are vulnerable to attacks due to a lack of standardized security measures. Unauthorized users could get access, compromise data, and even benefit from control of critical infrastructure. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system by designing a FLIP-based system that is highly scalable and adaptable. Utilizing a blockchain-based authentication mechanism with a multi-chain structure can provide additional security protection between different trust domains. Deep learning can be utilized to develop a network forensics framework with a high-performing system for detecting and tracking cyberattack incidents. Moreover, researchers should consider limiting the amount of data created and delivered when using big data to develop IoT-based smart systems. The findings of this review will stimulate academics to seek potential solutions for the identified issues, thereby advancing the IoT field.Comment: 77 pages, 5 figures, 5 table

GPT Models in Construction Industry: Opportunities, Limitations, and a Use Case Validation

Large Language Models(LLMs) trained on large data sets came into prominence in 2018 after Google introduced BERT. Subsequently, different LLMs such as GPT models from OpenAI have been released. These models perform well on diverse tasks and have been gaining widespread applications in fields such as business and education. However, little is known about the opportunities and challenges of using LLMs in the construction industry. Thus, this study aims to assess GPT models in the construction industry. A critical review, expert discussion and case study validation are employed to achieve the study objectives. The findings revealed opportunities for GPT models throughout the project lifecycle. The challenges of leveraging GPT models are highlighted and a use case prototype is developed for materials selection and optimization. The findings of the study would be of benefit to researchers, practitioners and stakeholders, as it presents research vistas for LLMs in the construction industry.Comment: 58 pages, 20 figure

Cyber-Physical Threat Intelligence for Critical Infrastructures Security

Modern critical infrastructures comprise of many interconnected cyber and physical assets, and as such are large scale cyber-physical systems. Hence, the conventional approach of securing these infrastructures by addressing cyber security and physical security separately is no longer effective. Rather more integrated approaches that address the security of cyber and physical assets at the same time are required. This book presents integrated (i.e. cyber and physical) security approaches and technologies for the critical infrastructures that underpin our societies. Specifically, it introduces advanced techniques for threat detection, risk assessment and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM), pen-testing, vulnerability assessment and security data analytics can be used in the context of integrated Critical Infrastructure Protection. The novel methods and techniques of the book are exemplified in case studies involving critical infrastructures in four industrial sectors, namely finance, healthcare, energy and communications. The peculiarities of critical infrastructure protection in each one of these sectors is discussed and addressed based on sector-specific solutions. The advent of the fourth industrial revolution (Industry 4.0) is expected to increase the cyber-physical nature of critical infrastructures as well as their interconnection in the scope of sectorial and cross-sector value chains. Therefore, the demand for solutions that foster the interplay between cyber and physical security, and enable Cyber-Physical Threat Intelligence is likely to explode. In this book, we have shed light on the structure of such integrated security systems, as well as on the technologies that will underpin their operation. We hope that Security and Critical Infrastructure Protection stakeholders will find the book useful when planning their future security strategies

WOPR: A Dynamic Cybersecurity Detection and Response Framework

Malware authors develop software to exploit the flaws in any platform and application which suffers a vulnerability in its defenses, be it through unpatched known attack vectors or zero-day attacks for which there is no current solution. It is the responsibility of cybersecurity personnel to monitor, detect, respond to and protect against such incidents that could affect their organization. Unfortunately, the low number of skilled, available cybersecurity professionals in the job market means that many positions go unfilled and cybersecurity threats are unknowingly allowed to negatively affect many enterprises.The demand for a greater cybersecurity posture has led several organizations to de- velop automated threat analysis tools which can be operated by less-skilled infor- mation security analysts and response teams. However, the diverse needs and organizational factors of most businesses presents a challenge for a “one size fits all” cybersecurity solution. Organizations in different industries may not have the same regulatory and standards compliance concerns due to processing different forms and classifications of data. As a result, many common security solutions are ill equipped to accurately model cybersecurity threats as they relate to each unique organization.We propose WOPR, a framework for automated static and dynamic analysis of software to identify malware threats, classify the nature of those threats, and deliver an appropriate automated incident response. Additionally, WOPR provides the end user the ability to adjust threat models to fit the risks relevant to an organization, allowing for bespoke automated cybersecurity threat management. Finally, WOPR presents a departure from traditional signature-based detection found in anti-virus and intrusion detection systems through learning system-level behavior and matching system calls with malicious behavior