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This paper aims to investigate the perceptions of financial accountants and both internal and external auditors regarding the impact of corporate governance (CG) and information technology (IT) on the detection and prevention of fraud within organizations.

Primary data were collected from 250 financial accountants, internal auditors and external auditors through questionnaires. The non-probability snowball sampling technique was used for data collection, with the sample t-test, one-way ANOVA and paired sample t-test applied for analysis.

The results indicate that robust CG practices and IT techniques significantly aid in detecting and reducing fraudulent activities by minimizing opportunities, rationalizations, pressures and capabilities of potential employees to commit fraud. Internal controls also play a significant role in reducing instances of fraud. Notably, ethical officers and ethical training were not perceived as significantly effective in preventing and detecting fraud, leading to a perception that fraudulent practices are prevalent and increasing the risk of future fraudulent activities.

This study recommends the adoption of strong CG practices to identify potential fraud within an organization. Moreover, IT techniques should be tailored to specific needs for effective utilization. Furthermore, the government should increase awareness regarding data provision by departments, organizations and other related personnel. Future research could use secondary data from various regions to expand the literature in this field.

This research uniquely combines three significant factors: CG, IT and forensic accounting in fraud detection and prevention. It contributes to the enhancement of literature about fraud and its preventive and detective measures. The results of this study set the seed for future research, government policymaking and enhanced organizational practices.

This paper aims to investigate the role of corporate governance and information technology in fraud prevention and detection within the United Arab Emirates (UAE).

This study uses a survey of financial accountants and internal and external auditors to assess their perceptions of the effectiveness of IT and corporate governance as measured in terms of the audit committee’s effectiveness, internal audit functions, external audit functions, culture of honesty and employee training programmes in preventing and detecting fraud in the UAE.

The results indicate that corporate governance has a moderate role in preventing and detecting fraud in the UAE and that IT has the same role as traditional fraud prevention and detection techniques. The results also show no significant difference between internal and external auditors in their use of technological and traditional techniques during the course of audits.

The findings suggest that the senior management and boards of directors must better understand the importance of their oversight function. The finding that a culture of honesty has a low positive impact on fraud prevention and detection in the UAE indicates that chief executive officers and boards of directors must make more efforts to set the “tone at the top” to improve the corporate environment in terms of integrity and ethics, among other factors. Furthermore, as IT and traditional techniques provide the same function, senior management and boards of directors must be alerted to the importance of developing systematic approaches to fraud investigation that involve greater reliance on technological approaches.

The moderate role of corporate governance suggests that senior management and boards of directors must better understand the importance of their oversight function to meet their obligations and fiduciary responsibilities to stakeholders. Furthermore, greater adoption of IT to detect and prevent fraud contributes to developing a systematic approach to fraud investigation, capable of identifying unusual activity using effective software.

This study contributes to the literature on the role of corporate governance and IT in preventing and detecting fraud, particularly for Middle Eastern countries and other emerging nations. The study may provide insights to academics and practitioners in the UAE and their international counterparts.

This paper aims to determine how forensic accounting contributes to fraud detection and prevention and answer the following research questions: What are the standard techniques for fraud detection and prevention; and What are the significant challenges that hinder the application of forensic accounting in fraud prevention and detection?

The authors use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to carry out a systematic literature review (SLR) to identify and assess the existing literature on forensic accounting.

There exists a positive correlation between forensic accounting and fraud detection and prevention. Moreover, in both the empirical and non-empirical findings, the authors note that fraud is complex, and in carrying out fraud investigations, one must be aware of its complexity.

Although drug counterfeiting is a sector where forensic accountants have paid less attention, it is a rapidly expanding fraud area. This paper finds that to detect fraud at an early stage, one must increase consumer understanding of basic forensic accounting techniques by implementing accurate supply chain monitoring systems and inventory management controls and conducting adequate and effective regulatory, honest and legitimate customs inspections.

The major factors that restrict forensic accounting are a lack of awareness and education. Hence, it is essential to incorporate forensic accounting in undergraduate and post-graduate courses.

From the existing literature, it has been observed that very few studies have been conducted in this field using the PRISMA and SLR techniques. Also, the authors carried out a holistic study that focuses on three different areas – fraud detection, fraud prevention and the challenges in forensic accounting.

Wireless multi-hop ad hoc networks are becoming very attractive and widely deployed in many kinds of communication and networking applications. However, distributed and collaborative routing in such networks makes them vulnerable to various security attacks. This paper aims to design and implement a new efficient intrusion detection and prevention framework, called EIDPF, a host-based framework suitable for mobile ad hoc network’s characteristics such as high node’s mobility, resource-constraints and rapid topology change. EIDPF aims to protect an AODV-based network against routing attacks that could target such network.

This detection and prevention framework is composed of three complementary modules: a specification-based intrusion detection system to detect attacks violating the protocol specification, a load balancer to prevent fast-forwarding attacks such as wormhole and rushing and adaptive response mechanism to isolate malicious node from the network.

A key advantage of the proposed framework is its capacity to efficiently avoid fast-forwarding attacks and its real-time detection of both known and unknown attacks violating specification. The simulation results show that EIDPF exhibits a high detection rate, low false positive rate and no extra communication overhead compared to other protection mechanisms.

It is a new intrusion detection and prevention framework to protect ad hoc network against routing attacks. A key strength of the proposed framework is its ability to guarantee a real-time detection of known and unknown attacks that violate the protocol specification, and avoiding wormhole and rushing attacks by providing a load balancing route discovery.

This study aims to present a novel system for detection and prevention of black hole and wormhole attacks in wireless sensor network (WSN) based on deep learning model. Here, different phases are included such as assigning the nodes, data collection, detecting black hole and wormhole attacks and preventing black hole and wormhole attacks by optimal path communication. Initially, a set of nodes is assumed for carrying out the communication in WSN. Further, the black hole attacks are detected by the Bait process, and wormhole attacks are detected by the round trip time (RTT) validation process. The data collection procedure is done with the Bait and RTT validation process with attribute information. The gathered data attributes are given for the training in which long short-term memory (LSTM) is used that includes the attack details. This is used for attack detection process. Once they are detected, those attacks are removed from the network using the optimal path selection process. Here, the optimal shortest path is determined by the improvement in the whale optimization algorithm (WOA) that is called as fitness rate-based whale optimization algorithm (FR-WOA). This shortest path communication is carried out based on the multi-objective function using energy, distance, delay and packet delivery ratio as constraints.

This paper implements a detection and prevention of attacks model based on FR-WOA algorithm for the prevention of attacks in the WSNs. With this, this paper aims to accomplish the desired optimization of multi-objective functions.

From the analysis, it is found that the accuracy of the optimized LSTM is better than conventional LSTM. The energy consumption of the proposed FR-WOA with 35 nodes is 7.14% superior to WOA and FireFly, 5.7% superior to grey wolf optimization and 10.3% superior to particle swarm optimization.

This paper develops the FR-WOA with optimized LSTM detecting and preventing black hole and wormhole attacks from WSN. To the best of the authors’ knowledge, this is the first work that uses FR-WOA with optimized LSTM detecting and preventing black hole and wormhole attacks from WSN.

Healthcare practitioners (HCPs) have a major responsibility in the prevention and early detection of oral cancer (OC). Accordingly, adequate training in this area will positively enhance healthcare practitioners' accountability towards their patients. The present study was conducted in Saudi Arabia with the objective of assessing HCPs' opinion vis‐à‐vis OC prevention and early detection.

A cross‐sectional survey was distributed among HCPs in six different settings in Saudi Arabia.

Totals of 41.2 per cent and 63.4 per cent of HCPs thought that they are adequately trained to perform an OC examination and to palpate the lymph nodes, respectively. Similarly, 33.2 per cent and 25.8 per cent thought that they are adequately trained to provide tobacco and alcohol cessation education for their patients, respectively. Of HCPs, 45.1 per cent thought they had a low level of knowledge and training in OC prevention and the early detection thereof, 53.6 per cent agreed that their knowledge about OC was not current, and 82 per cent were comfortable with referring suspicious lesions to specialists.

It appears that the current knowledge and training in OC prevention and early detection among HCPs in Saudi Arabia is not up to the desired level. Accordingly, it is suggested that OC prevention and early detection should be given the necessary attention when establishing new continuous education strategies in Saudi Arabia.

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.

Nowadays, more interest is found among the researchers in MANETs in practical and theoretical areas and their performance under various environments. WSNs have begun to combine with the IoT via the sensing capability of Internet-connected devices and the Internet access ability of sensor nodes. It is essential to shelter the network from attacks over the Internet by keeping the secure router.

This paper plans to frame an effective literature review on diverse intrusion detection and prevention systems in Wireless Sensor Networks (WSNs) and Mobile Ad hoc NETworks (MANETs) highly suitable for security in Internet of Things (IoT) applications. The literature review is focused on various types of attacks concentrated in each contribution and the adoption of prevention and mitigation models are observed. In addition, the types of the dataset used, types of attacks concentrated, types of tools used for implementation, and performance measures analyzed in each contribution are analyzed. Finally, an attempt is made to conclude the review with several future research directions in designing and implementing IDS for MANETs that preserve the security aspects of IoT.

It observed the different attack types focused on every contribution and the adoption of prevention and mitigation models. Additionally, the used dataset types, the focused attack types, the tool types used for implementation, and the performance measures were investigated in every contribution.

This paper presents a literature review on diverse contributions of attack detection and prevention, and the stand of different machine learning and deep learning models along with the analysis of types of the dataset used, attacks concentrated, tools used for implementation and performance measures on the network security for IoT applications.

The purpose of this paper is to mitigate vulnerabilities in web applications, security detection and prevention are the most important mechanisms for security. However, most existing research focuses on how to prevent an attack at the web application layer, with less work dedicated to setting up a response action if a possible attack happened.

A combination of a Signature-based Intrusion Detection System (SIDS) and an Anomaly-based Intrusion Detection System (AIDS), namely, the Intelligent Intrusion Detection and Prevention System (IIDPS).

After evaluating the new system, a better result was generated in line with detection efficiency and the false alarm rate. This demonstrates the value of direct response action in an intrusion detection system.

Data limitation.

The contributions of this paper are to first address the problem of web application vulnerabilities. Second, to propose a combination of an SIDS and an AIDS, namely, the IIDPS. Third, this paper presents a novel approach by connecting the IIDPS with a response action using fuzzy logic. Fourth, use the risk assessment to determine an appropriate response action against each attack event. Combining the system provides a better performance for the Intrusion Detection System, and makes the detection and prevention more effective.

This paper examines the role of professional associations, governmental agencies, and international accounting and auditing bodies in promulgating standards to deter and detect fraud, domestically and abroad. Specifically, it focuses on the role played by the US Securities and Exchange Commission (SEC), the American Institute of Certified Public Accountants (AICPA), the Institute of Internal Auditors (IIA), the Institute of Management Accountants (IMA), the Association of Certified Fraud Examiners (ACFE), the US Government Accounting Office (GAO), and other national and foreign professional associations, in promulgating auditing standards and procedures to prevent fraud in financial statements and other white‐collar crimes. It also examines several fraud cases and the impact of management and employee fraud on the various business sectors such as insurance, banking, health care, and manufacturing, as well as the role of management, the boards of directors, the audit committees, auditors, and fraud examiners and their liability in the fraud prevention and investigation.