Search Results (20)

The malicious contamination of food has been recognized by the World Health Organization (WHO) as a real and current threat that must be integrated into food safety systems to ensure preparedness for deliberate attacks. Traditional approaches, such as HACCP, effectively address unintentional hazards but remain insufficient against intentional contamination and sabotage. Food defense frameworks such as HACCP (Hazard Analysis and Critical Control Points), VACCP (Vulnerability Assessment and Critical Control Points), and TACCP (Threat Assessment and Critical Control Points) represent complementary methodologies, addressing unintentional, economically motivated, and deliberate threats, respectively. This review critically examines food defense frameworks across the European Union, the United States, and the United Kingdom, as well as standards benchmarked by the Global Food Safety Initiative (GFSI), drawing on peer-reviewed and grey literature sources. In the United States, the Food Safety Modernization Act (FSMA) mandates the development and periodic reassessment of food defense plans, while the European Union primarily relies on general food law and voluntary certification schemes. The United Kingdom’s PAS 96:2017 standard provides TACCP-based guidance that also acknowledges cybercrime as a deliberate threat. Building on these regulatory and operational gaps, this paper proposes the Cyber-FSMS model, an integrated framework that combines traditional food defense pillars with cyber risk management to address cyber–physical vulnerabilities in increasingly digitalized supply chains. The model introduces six interconnected components (governance, vulnerability assessment, mitigation, monitoring, verification, and recovery) designed to embed cyber-resilience into Food Safety Management Systems (FSMS). Priority actions include regulatory harmonization, practical support for small and medium-sized enterprises (SMEs), and the alignment of cyber-resilience principles with upcoming GFSI benchmarking developments, thereby strengthening the integrity, robustness, and adaptability of global food supply chains. Full article

This paper examines the risks linked to E-business collaboration between China and West Africa, with particular emphasis on Ghana as a pivotal digital commerce centre. This research employs the Hesitant Fuzzy Best–Worst Method (HF-BWM) to systematically identify and prioritise the institutional, technological, sociocultural, and legal issues affecting cross-border e-business operations. This study combines Transaction Cost Theory (TCT), the Technology Acceptance Model (TAM), and Commitment–Trust Theory to create a comprehensive framework for analysing the interplay of these risks and their effects on transaction costs and company sustainability. The findings indicate that institutional risks constitute the most substantial obstacles, with deficient digital transaction legislation and inadequate data governance recognised as the principal drivers of uncertainty and increased transaction costs. The research indicates that these institutional challenges necessitate immediate focus, as they immediately affect corporate operations, especially in international digital commerce. Technological risks, such as cybersecurity vulnerabilities, insufficient IT skills, and deficiencies in digital infrastructure, were identified as the second most critical factors, leading to considerable operational disruptions and heightened expenses. Sociocultural hazards, such as language difficulties and varying consumer behaviours, were recognised as moderate concerns that, although significant, exert a weaker cumulative impact than technological and institutional challenges. Eventually, legal risks, especially concerning cybercrime legislation and the protection of intellectual property, were identified as substantial complicators of e-business activities, increasing the intricacy of legal compliance and cross-border contract enforcement. The results underscore the imperative for regulatory reforms, investments in cybersecurity, and methods for cultural adaptation to alleviate the identified risks and promote sustainable growth in China–West Africa e-business relationships. This study offers practical insights for governments, business leaders, and investors to effectively manage the intricate risk landscape and make educated decisions that foster enduring collaboration and trust between China and West Africa in digital trade. Full article

As cyber threats escalate in scale and sophistication, the imperative to secure public data through theoretically grounded and practically viable frameworks becomes increasingly urgent. This review investigates whether and how criminology theories have effectively informed the development and implementation of information security management frameworks (ISMFs) to prevent cybercrime and fortify the digital ecosystem’s resilience. Anchored in a comprehensive bibliometric analysis of 617 peer-reviewed records extracted from Scopus and Web of Science, the study employs Multiple Correspondence Analysis (MCA), conceptual co-word mapping, and citation coupling to systematically chart the intellectual landscape bridging criminology and cybersecurity. The review reveals those foundational criminology theories—particularly routine activity theory, rational choice theory, and deterrence theory—have been progressively adapted to cyber contexts, offering novel insights into offender behaviour, target vulnerability, and systemic guardianship. In parallel, the study critically engages with global cybersecurity standards such as National Institute of Standards and Technology (NIST) and ISO, to evaluate how criminological principles are embedded in practice. Using data from the Global Cybersecurity Index (GCI), the paper introduces an innovative visual mapping of the divergence between cybersecurity preparedness and digital development across 170+ countries, revealing strategic gaps and overperformers. This paper ultimately argues for an interdisciplinary convergence between criminology and cybersecurity governance, proposing that the integration of criminological logic into cybersecurity frameworks can enhance risk anticipation, attacker deterrence, and the overall security posture of digital public infrastructures. Full article

In recent years, there has been a sharp increase in the number of online fraud cases. However, research on crime geography has paid little attention to online crimes, especially to the influencing factors behind their spatial distributions. Online fraud is closely related to people’s daily internet use. The existing literature has explored the impact of internet use on online crimes based on small samples of individual interviews. There is a lack of large-scale studies from a community perspective. This study applies the routine activity theory to online activities to test the relationship between online fraud alert data and the usage durations of different types of mobile phone users’ applications (apps) for communities in ZG City. It builds negative binomial regression models for analyzing the impact of the usage of different types of apps on the spatial distribution of online fraud. The results reveal that the online fraud crime rate and the online time spent on a financial management app share the most similar spatial distribution. While financial management, online education, transportation, and search engine app usages have a significant positive association with online fraud, the use of a financial management app has the greatest impact. Additionally, time spent on social media, online shopping and entertainment, and mobile reading apps have a significant negative association with online fraud. As not all online activities lead to cybercrime, crime prevention efforts should target specific types of apps, such as financial management, online education, transportation, and search engines. Full article

Cybercrime prevention is critical for the effective functioning of e-government services. Despite its importance, internal cybercrime mitigation processes within these services are underrepresented in the existing literature. This study addresses this gap by conducting a systematic review and bibliometric analysis of e-government research from January 2015 to January 2025. Using the Web of Science and Scopus databases, 3790 studies were identified; after removing duplicates, bibliometric analysis was performed using R Studio (Build 467). The analysis revealed that Government Information Quarterly was the leading journal, with China, the USA, and the UK contributing the most publications. Nineteen major themes emerged, with “adoption” identified as the dominant theme, followed by “governance” and “development”. Among 88 security-related studies, 19 specifically addressed cybersecurity in e-government services. Findings indicate a predominant focus on user-centric perspectives, such as service adoption and system vulnerabilities, while internal cybersecurity issues, including managerial practices and mitigation strategies, remain largely unexplored. Limited data availability may contribute to this gap. This study highlights the need for future research to adopt an integrated approach, emphasising management-level practices for cybercrime mitigation within e-government institutions from both developing and developed nations. Full article

Digital evidence plays a crucial role in cybercrime investigations by linking individuals to criminal activities. Data collection, preservation, and analysis can benefit from emerging technologies like blockchain to provide a secure, distributed ledger for managing digital evidence. This study proposes a blockchain-based solution for managing digital evidence in cybercrime cases in the judicial domain. The proposed solution provides the basis for the development of a new model that leverages a consortium blockchain, allowing secure collaboration among judicial stakeholders, while ensuring data integrity and admissibility in court. An extensive literature review demonstrates blockchain’s potential to create a more secure, efficient evidence management system. The proposed model was implemented in a test environment using a localised blockchain for developing and testing smart contracts, as well as integrating a web interface, with off-chain storage for managing evidence data. The system was subsequently deployed in both the Polygon and Ethereum test networks, simulating real-world blockchain environments, revealing that the operational cost in the Polygon network is reduced by 99.96% compared to Ethereum, thereby offering scalability without compromising security. This study underscores blockchain’s potential to revolutionise the chain of custody procedures, improving dependability and security in evidence management and providing more sustainable solutions within the criminal justice system. Full article

This review addresses the fragmented literature on administrative interventions for cybercrime mitigation within e-government services, which often prioritise technological aspects over a unified theoretical framework. By analysing 32 peer-reviewed articles from the Web of Science (WoS) and Scopus databases, supplemented by additional sources located through Google Scholar, this study synthesises factors within the technical, managerial and behavioural domains using the Theory, Context and Method (TCM) framework. The findings reveal a predominant focus on managerial and technical factors, with behavioural aspects frequently overlooked. Cybercrime mitigation is often treated as a procedural step rather than a holistic process. This study advocates a well-established, context-specific mitigation plan, integrating regional factors through the Human–Organisation–Technology (HOT) framework to develop a comprehensive model for effective cybercrime mitigation in e-government services. This research has practical, theoretical and policy implications, offering actionable insights for improving operational practices, advancing theoretical frameworks and guiding policymakers in formulating effective cybercrime mitigation strategies. Full article

The surge in big data and analytics has catalysed the proliferation of cybercrime, largely driven by organisations’ intensified focus on gathering and processing personal data for profit while often overlooking security considerations. Hadoop and its derivatives are prominent platforms for managing big data; however, investigating security incidents within Hadoop environments poses intricate challenges due to scale, distribution, data diversity, replication, component complexity, and dynamicity. This paper proposes a big data digital forensics readiness framework and an incident response script for Linux–Hadoop environments, streamlining preliminary investigations. The framework offers a novel approach to digital forensics in the domains of big data and Hadoop environments. A prototype of the incident response script for Linux–Hadoop environments was developed and evaluated through comprehensive functionality and usability testing. The results demonstrated robust performance and efficacy. Full article

Cyber threats are attempts to secure unauthorized access to, change, or delete private information, to demand money from victims, or to disrupt business. Cybercrime includes everything from identity theft, malware threats, email and online fraud, to bank fraud. Businesses and individuals use this method to guard their data centers and other digital systems. The lack of scalability, sluggish response times, and inability to spot advanced and insider threats are among some of the problems with conventional approaches to network security. These flaws highlight the need for research to build more efficient and all-encompassing security methods to guard against the expanding variety of network attacks. Cybercriminals use AI and data poisoning, as well as model theft strategies to automate their attacks. A cyber security technique based on artificial intelligence is presented in this study for financial sector management (CS-FSM). In order to map and prevent unexpected risks from devouring a business, artificial intelligence is one of the best technologies. Using the proposed technique, cyberattack problems can be classified and solved. To ensure the security of financial sector information, algorithms such as the Enhanced Encryption Standard (EES) encrypt and decrypt data. By learning from the training data, the K-Nearest Neighbor (KNN) algorithm produces predictions. In the financial sector, it is used to detect and stop malware attacks. The proposed method increases cyber security systems’ performance by increasing their defense against cyberattacks. CS-FSM enhances data privacy (18.3%), scalability (17.2%), risk reduction (13.2%), data protection (16.2%), and attack avoidance (11.2%) ratios. Full article

The Metaverse is a multi-user virtual world that combines physical reality with digital virtual reality. The three basic technologies for building the Metaverse are immersive technologies, artificial intelligence, and blockchain. Companies are subsequently making significant investments into creating an artificially intelligent Metaverse, with the consequence that cybersecurity has become more crucial. As cybercrime increases exponentially, it is evident that a comprehensive study of Metaverse security based on artificial intelligence is lacking. A growing number of distributed denial-of-service attacks and theft of user identification information makes it necessary to conduct comprehensive and inclusive research in this field in order to identify the Metaverse’s vulnerabilities and weaknesses. This article provides a summary of existing research on AI-based Metaverse cybersecurity and discusses relevant security challenges. Based on the results, the issue of user identification plays a very important role in the presented works, for which biometric methods are the most commonly used. While the use of biometric data is considered the safest method, due to their uniqueness, they are also susceptible to misuse. A cyber-situation management system based on artificial intelligence should be able to analyze data of any volume with the help of algorithms. To prepare researchers who will pursue this topic in the future, this article provides a comprehensive summary of research on cybersecurity in the Metaverse based on artificial intelligence. Full article

Intelligent software packages have become fast-growing in popularity for large businesses in both developed and developing countries, due to their higher availability in detecting and preventing cybercrime. However, small and medium enterprises (SMEs) are showing prominent gaps in this adoption due to their level of awareness and knowledge towards cyber security and the security mindset. This is due to their priority of running their businesses over requiring using the right technology in protecting their data. This study explored how SMEs in Wales are handling cybercrime and managing their daily online activities the best they can, in keeping their data safe in tackling cyber threats. The sample collected consisted of 122 Welsh SME respondents in a collection of data through a survey questionnaire. The results and findings showed that there were large gaps in the awareness and knowledge of using intelligent software, in particular the uses of machine learning integration within their technology to track and combat complex cybercrime that perhaps would have been missed by standard cyber security software packages. The study’s findings showed that only 30% of the sampled SMEs understood the terminology of cyber security. The awareness of machine learning and its algorithms was also questioned in the implementation of their cyber security software packages. The study further highlighted that Welsh SMEs were unaware of what this software could do to protect their data. The findings in this paper also showed that various elements such as education and the size of SME made an impact on their choices for the right software packages being implemented, compared to elements such as age, gender, role and being a decision maker, having no impact on these choices. The study finally shares the investigations of various SME strategies to help understand the risks, and to be able to plan for future contingencies and preparation in keeping data safe and secure for the future. Full article

A wide range of recent studies are focusing on current issues of financial fraud, especially concerning cybercrimes. The reason behind this is even with improved security, a great amount of money loss occurs every year due to credit card fraud. In recent days, ATM fraud has decreased, while credit card fraud has increased. This study examines articles from five foremost databases. The literature review is designed using extraction by database, keywords, year, articles, authors, and performance measures based on data used in previous research, future research directions and purpose of the article. This study identifies the crucial gaps which ultimately allow research opportunities in this fraud detection process by utilizing knowledge from the machine learning domain. Our findings prove that this research area has become most dominant in the last ten years. We accessed both supervised and unsupervised machine learning techniques to detect cybercrime and management techniques which provide evidence for the effectiveness of machine learning techniques to control cybercrime in the credit card industry. Results indicated that there is room for further research to obtain better results than existing ones on the basis of both quantitative and qualitative research analysis. Full article

Despite the focus on knowledge risks in the literature, a limited number of studies have empirically examined technological knowledge risks in terms of digitalization, old technologies, and cybercrime as moderating variables in the relationship between work-life balance and job performance. To address this gap, this paper investigated the moderation effects of technological knowledge risks on the relationship between work-life balance and job performance during the pandemic period in employees of cooperative credit banks. A quantitative approach that involved gathering surveys was adopted. Applying PLS-SEM, the empirical findings revealed that technological knowledge risks have a significant impact on the relationship between work-life balance and job performance. Additionally, this research encourages managers to create and maintain a healthy work environment that promotes valuable employees’ job performance while also evaluating the use of new technological advances and their related risks. Full article

The COVID-19 pandemic has brought massive online activities and increased cybersecurity incidents and cybercrime. As a result of this, the cyber reputation of organisations has also received increased scrutiny and global attention. Due to increased cybercrime, reputation displaying a more important role within risk management frameworks both within public and private institutions is vital. This study identifies key factors in determining reputational damage to public and private sector institutions through cyberattacks. Researchers conducted an extensive review of the literature, which addresses factors relating to risk management of reputation post-cyber breach. The study identified 42 potential factors, which were then classified using the STAR model. This model is an organisational design framework and was suitable due to its alignment with organisations. A qualitative study using semi-structured and structured questions was conducted with purposively selected cybersecurity experts in both public and private sector institutions. Data obtained from the expert forum were analysed using thematic analysis, which revealed that a commonly accepted definition for cyber reputation was lacking despite the growing use of the term “online reputation”. In addition, the structured questions data were analysed using relative importance index rankings. The analysis results revealed significant factors in determining reputational damage due to cyberattacks, as well as highlighting reputation factor discrepancies between private and public institutions. Theoretically, this study contributes to the body of knowledge relating to cybersecurity of organisations. Practically, this research is expected to aid organisations to properly position themselves to meet cyber incidents and become more competitive in the post-COVID-19 era. Full article

In many developed countries, the usage of artificial intelligence (AI) and machine learning (ML) has become important in paving the future path in how data is managed and secured in the small and medium enterprises (SMEs) sector. SMEs in these developed countries have created their own cyber regimes around AI and ML. This knowledge is tested daily in how these countries’ SMEs run their businesses and identify threats and attacks, based on the support structure of the individual country. Based on recent changes to the UK General Data Protection Regulation (GDPR), Brexit, and ISO standards requirements, machine learning cybersecurity (MLCS) adoption in the UK SME market has become prevalent and a good example to lean on, amongst other developed nations. Whilst MLCS has been successfully applied in many applications, including network intrusion detection systems (NIDs) worldwide, there is still a gap in the rate of adoption of MLCS techniques for UK SMEs. Other developed countries such as Spain and Australia also fall into this category, and similarities and differences to MLCS adoptions are discussed. Applications of how MLCS is applied within these SME industries are also explored. The paper investigates, using quantitative and qualitative methods, the challenges to adopting MLCS in the SME ecosystem, and how operations are managed to promote business growth. Much like security guards and policing in the real world, the virtual world is now calling on MLCS techniques to be embedded like secret service covert operations to protect data being distributed by the millions into cyberspace. This paper will use existing global research from multiple disciplines to identify gaps and opportunities for UK SME small business cyber security. This paper will also highlight barriers and reasons for low adoption rates of MLCS in SMEs and compare success stories of larger companies implementing MLCS. The methodology uses structured quantitative and qualitative survey questionnaires, distributed across an extensive participation pool directed to the SMEs’ management and technical and non-technical professionals using stratify methods. Based on the analysis and findings, this study reveals that from the primary data obtained, SMEs have the appropriate cybersecurity packages in place but are not fully aware of their potential. Secondary data collection was run in parallel to better understand how these barriers and challenges emerged, and why the rate of adoption of MLCS was very low. The paper draws the conclusion that help through government policies and processes coupled together with collaboration could minimize cyber threats in combatting hackers and malicious actors in trying to stay ahead of the game. These aspirations can be reached by ensuring that those involved have been well trained and understand the importance of communication when applying appropriate safety processes and procedures. This paper also highlights important funding gaps that could help raise cyber security awareness in the form of grants, subsidies, and financial assistance through various public sector policies and training. Lastly, SMEs’ lack of understanding of risks and impacts of cybercrime could lead to conflicting messages between cross-company IT and cybersecurity rules. Trying to find the right balance between this risk and impact, versus productivity impact and costs, could lead to UK SMES getting over these hurdles in this cyberspace in the quest for promoting the usage of MLCS. UK and Wales governments can use the research conducted in this paper to inform and adapt their policies to help UK SMEs become more secure from cyber-attacks and compare them to other developed countries also on the same future path. Full article