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To protect information and communication technology (ICT) infrastructure and resources against poor cyber hygiene behaviours, organisations commonly require internal users to confirm they will abide by an ICT Code of Conduct. Before commencing enrolment, university students sign ICT policies, however, individuals can ignore or act contrary to these policies. This study aims to evaluate whether students can apply ICT Codes of Conduct and explores viable approaches for ensuring that students understand how to act ethically and in accordance with such codes.

The authors designed a between-subjects experiment involving 260 students’ responses to five scenario-pairs that involve breach/non-breach of a university’s ICT policy following a priming intervention to heighten awareness of ICT policy or relevant ethical principles, with a control group receiving no priming.

This study found a significant difference in students’ responses to the breach versus non-breach cases, indicating their ability to apply the ICT Code of Conduct. Qualitative comments revealed the priming materials influenced their reasoning.

The authors’ priming interventions were inadequate for improving breach recognition compared to the control group. More nuanced and targeted priming interventions are suggested for future studies.

Appropriate application of ICT Code of Conduct can be measured by collecting student/employee responses to breach/non-breach scenario pairs based on the Code and embedded with ethical principles.

Shared awareness and protection of ICT resources.

Compliance with ICT Codes of Conduct by students is under-investigated. This study shows that code-based scenarios can measure understanding and suggest that targeted priming might offer a non-resource intensive training approach.

Based on this holistic model, the authors propose and analyze seven key issues related to the admissibility of digital media in cross-border trials considering four Latin American countries.

The authors apply the modeling process of the soft systems methodology by Checkland in order to develop a holistic model focused on human situation problems involving digital media and information technology devices or systems.

The authors discuss the status of the identified key issues in each country and offer a perspective on the integration of cross-border work analyzing the contribution of these key issues to the collaboration between countries criminal cases or the use of foreign digital artifacts in domestic trials.

In this study, the authors assumed that the problems of official interaction between agencies of different countries are considered solved. However, for future studies or research, the authors recommend that these issues can be considered as relevant, since they are related to cross-border cooperation topics that will necessarily require unavoidable official arrangements, agreements and formalities.

This work is aimed at defining and analyzing the key issues that can contribute to the application of current techniques and methodologies in digital forensics as a tool to support the legal framework of each country, considering cross-border trials. Finally, the authors highlight the implications of this study lie in the identification and analysis of the key issues that must be considered for digital forensics as a support tool for the admissibility of digital evidence in cross-border trials.

The authors consider that digital forensic will have high demand in cross-border trials, and it will depend on the people mobility between the countries considered in this study.

This paper shows that the soft systems methodology allows elaborating a holistic model focused on social problems involving digital media and informatics devices.

The spread of Covid-19 has led to the closure of educational institutions worldwide, forcing academic institutions to find online platforms. The purpose of this paper is to accelerate the development of the online learning (OL) environments within those institutions. The Covid-19 pandemic has unfolded the extent of the academic institutions' readiness to deal with such a crisis.

In this vein, the study aimed to identify the perception of translation instructors in teaching translation courses online during Covid-19, using a questionnaire to explore the strategies and challenges of teaching and assessing students' performance. The analysis revealed instructors' reliance on Zoom and Microsoft Teams in offering virtual classes and WhatsApp in communication with students outside the class.

The findings revealed the relative effectiveness of online education, but its efficacy is less than face-to-face learning according to the respondents' views. It was also found that students faced difficulties in OL, which lie in adapting to the online environment, lack of interaction and motivation and the deficiency of data connections. Even though online education could work as an aid during Covid-19, but it could not replace face-to-face instruction. Based on the findings, the study recommended blended learning. Combining online education with face-to-face instruction, i.e. face-to-face plus synchronous and asynchronous, would result in a rigorous OL environment.

The research is genuine and there is no conflict of interest.

This study aims to critically analyse the Law 9 January 2019, n. 3, on “Measures to fight crimes against the public administration and on the transparency of political parties and movements” (so-called bribe-destroyer law).

This paper draws on reports, legal scholarship and other open-source data to examine a legislative innovation for the corruption in Italy in relation to the general guarantees of the trial process and with the controversial paradigm of the national perception index of bribery.

The Italian legislative initiative that will be examined is innovative in nature and goes beyond the constitutional and conventional principles on procedural guarantees. The new initiative needs to be integrated into the international and European action against bribery that targets criminal proceeds, and at the same time, be anchored in respect for human rights during the process.

The new initiative needs to be integrated into the international and European action against bribery that targets criminal proceeds, and at the same time, be anchored in respect for human rights during the process.

Despite the aggressiveness and lofty proclamations by those who aspire to fight corruption from the highest levels, the goal of rehabilitating Italy from one of the seven “deadly sins” that delay economic growth still seems far off.

In the absence of public ethics, the increase in criminalisation does not seem sufficient on its own to guarantee the containment of the phenomenon.

This study examines the strengths and weaknesses of the important new law, its compatibility with human rights standards and its relationship to international standards of anti-bribery policies. The aggressive legislation critically relies on the pervasive and persistent lack of perception of corruption as a crime. In the confiscation (and now also reparation) of equivalent that normally addresses assets accumulated in a lawful manner, the periculum is even presumed in re ipsa and the classical aims of caution undergo a total torsion revealing an authoritarian face that takes on the meaning of anticipating further sanctioning contents. Finally, the presence of many levels of sanctioning in relation to the same fact poses serious problems of violation of the ne bis in idem rule.

This paper aims to update the cybersecurity-related accounting literature by synthesizing 39 recent theoretical and empirical studies on the topic. Furthermore, the paper provides a set of categories into which the studies fit.

This is a synthesis paper that summarizes the research literature on cybersecurity, introducing knowledge from the extant research and revealing areas requiring further examination.

This synthesis identifies a research framework that consists of the following research themes: cybersecurity and information sharing, cybersecurity investments, internal auditing and controls related to cybersecurity, disclosure of cybersecurity activities and security threats and security breaches.

Academics, practitioners and the public would benefit from a research framework that categorizes the research topics related to cybersecurity in the accounting field. This type of analysis is vital to enhance the understanding of the academic research on cybersecurity and can be used to support the identification of new lines for future research.

This is the first literature analysis of cybersecurity in the accounting field, and it has significant implications for research and practice by detailing, for example, the benefits of and obstacles to information sharing. This synthesis also highlights the importance of the model for cybersecurity investments. Further, the review emphasizes the role of internal auditing and controls to improve cybersecurity.

With the popularity of the internet and the increasing numbers of netizens, tremendous information flows are generated daily by the intelligently interconnected individuals. The diffusion processes of different information are not independent, and they interact with and influence each other. Modeling and analyzing the interaction between correlated information play an important role in the understanding of the characteristics of information dissemination and better control of the information flows. This paper aims to model the correlated information diffusion process over the crowd intelligence networks.

This study extends the classic epidemic susceptible–infectious–recovered (SIR) model and proposes the SIR mixture model to describe the diffusion process of two correlated pieces of information. The whole crowd is divided into different groups with respect to their forwarding state of the correlated information, and the transition rate between different groups shows the property of each piece of information and the influences between them.

The stable state of the SIR mixture model is analyzed through the linearization of the model, and the stable condition can be obtained. Real data are used to validate the SIR mixture model, and the detailed diffusion process of correlated information can be inferred by the analysis of the parameters learned through fitting the real data into the SIR mixture model.

The proposed SIR mixture model can be used to model the diffusion of correlated information and analyze the propagation process.

With the recent development of science and technology, research on information diffusion has become increasingly important.

To analyze the process of information diffusion, researchers have proposed a framework with graphical evolutionary game theory (EGT) according to the theory of biological evolution.

Through this method, one can study and even predict information diffusion.

This paper summarizes three existing works using graphical EGT to discuss how to obtain the static state and the dynamics of information diffusion in social network.

With the rapid development of internet technology, open online social networks provide a broader platform for information spreading. While dissemination of information provides convenience for life, it also brings many problems such as security risks and public opinion orientation. Various negative, malicious and false information spread across regions, which seriously affect social harmony and national security. Therefore, this paper aims to minimize negative information such as online rumors that has attracted extensive attention. The most existing algorithms for blocking rumors have prevented the spread of rumors to some extent, but these algorithms are designed based on entire social networks, mainly focusing on the microstructure of the network, i.e. the pairwise relationship or similarity between nodes. The blocking effect of these algorithms may be unsatisfactory in some networks because of the sparse data in the microstructure.

An algorithm for minimizing the influence of dynamic rumor based on community structure is proposed in this paper. The algorithm first divides the network into communities, and integrates the influence of each node within communities and rumor influence probability to measure the influence of each node in the entire network, and then selects key nodes and bridge nodes in communities as blocked nodes. After that, a dynamic blocking strategy is adopted to improve the blocking effect of rumors.

Community structure is one of the most prominent features of networks. It reveals the organizational structure and functional components of a network from a mesoscopic level. The utilization of community structure can provide effective and rich information to solve the problem of data sparsity in the microstructure, thus effectively improve the blocking effect. Extensive experiments on two real-world data sets have validated that the proposed algorithm has superior performance than the baseline algorithms.

As an important research direction of social network analysis, rumor minimization has a profound effect on the harmony and stability of society and the development of social media. However, because the rumor spread has the characteristics of multiple propagation paths, fast propagation speed, wide propagation area and time-varying, it is a huge challenge to improve the effectiveness of the rumor blocking algorithm.

The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control.

It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.

By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states.

In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.