Federated learning is an important distributed model training technique in Internet of Things(IoT),in which participant selection is a key component that plays a role in improving training efficiency and model accurac...Federated learning is an important distributed model training technique in Internet of Things(IoT),in which participant selection is a key component that plays a role in improving training efficiency and model accuracy.This module enables a central server to select a subset of participants to performmodel training based on data and device information.By doing so,selected participants are rewarded and actively perform model training,while participants that are detrimental to training efficiency and model accuracy are excluded.However,in practice,participants may suspect that the central server may have miscalculated and thus not made the selection honestly.This lack of trustworthiness problem,which can demotivate participants,has received little attention.Another problem that has received little attention is the leakage of participants’private information during the selection process.We will therefore propose a federated learning framework with auditable participant selection.It supports smart contracts in selecting a set of suitable participants based on their training loss without compromising the privacy.Considering the possibility of malicious campaigning and impersonation of participants,the framework employs commitment schemes and zero-knowledge proofs to counteract these malicious behaviors.Finally,we analyze the security of the framework and conduct a series of experiments to demonstrate that the framework can effectively improve the efficiency of federated learning.展开更多
Currently,there is a growing trend among users to store their data in the cloud.However,the cloud is vulnerable to persistent data corruption risks arising from equipment failures and hacker attacks.Additionally,when ...Currently,there is a growing trend among users to store their data in the cloud.However,the cloud is vulnerable to persistent data corruption risks arising from equipment failures and hacker attacks.Additionally,when users perform file operations,the semantic integrity of the data can be compromised.Ensuring both data integrity and semantic correctness has become a critical issue that requires attention.We introduce a pioneering solution called Sec-Auditor,the first of its kind with the ability to verify data integrity and semantic correctness simultaneously,while maintaining a constant communication cost independent of the audited data volume.Sec-Auditor also supports public auditing,enabling anyone with access to public information to conduct data audits.This feature makes Sec-Auditor highly adaptable to open data environments,such as the cloud.In Sec-Auditor,users are assigned specific rules that are utilized to verify the accuracy of data semantic.Furthermore,users are given the flexibility to update their own rules as needed.We conduct in-depth analyses of the correctness and security of Sec-Auditor.We also compare several important security attributes with existing schemes,demonstrating the superior properties of Sec-Auditor.Evaluation results demonstrate that even for time-consuming file upload operations,our solution is more efficient than the comparison one.展开更多
With the intelligentization of the Internet of Vehicles(lovs),Artificial Intelligence(Al)technology is becoming more and more essential,especially deep learning.Federated Deep Learning(FDL)is a novel distributed machi...With the intelligentization of the Internet of Vehicles(lovs),Artificial Intelligence(Al)technology is becoming more and more essential,especially deep learning.Federated Deep Learning(FDL)is a novel distributed machine learning technology and is able to address the challenges like data security,privacy risks,and huge communication overheads from big raw data sets.However,FDL can only guarantee data security and privacy among multiple clients during data training.If the data sets stored locally in clients are corrupted,including being tampered with and lost,the training results of the FDL in intelligent IoVs must be negatively affected.In this paper,we are the first to design a secure data auditing protocol to guarantee the integrity and availability of data sets in FDL-empowered IoVs.Specifically,the cuckoo filter and Reed-Solomon codes are utilized to guarantee error tolerance,including efficient corrupted data locating and recovery.In addition,a novel data structure,Skip Hash Table(SHT)is designed to optimize data dynamics.Finally,we illustrate the security of the scheme with the Computational Diffie-Hellman(CDH)assumption on bilinear groups.Sufficient theoretical analyses and performance evaluations demonstrate the security and efficiency of our scheme for data sets in FDL-empowered IoVs.展开更多
This paper aims to investigate the effect of the characteristics of the internal audit function(IAF)on earnings management(EM)for a sample of 27 Tunisian listed companies.The authors employed the Correlated Panels Cor...This paper aims to investigate the effect of the characteristics of the internal audit function(IAF)on earnings management(EM)for a sample of 27 Tunisian listed companies.The authors employed the Correlated Panels Corrected Standard Errors model to estimate the regression equation.The results showed that EM is negatively associated with internal audit effectiveness,frequency of audit committee meetings with Chief Audit Executives(CAEs),the partial outsourcing of internal audit,and the firm’s size.Moreover,the authors found a positive relationship between EM and the use of IAF as a training ground for management and the private sector.This study is important to academics,regulators,and policymakers in introducing new governance reforms to strengthen the IAF as an important internal governance mechanism to reduce earnings management practices in emerging countries.The results also provide useful information for investors to examine the effect of internal audit characteristics on earnings management.展开更多
The aim of this study is to examine the qualities that auditors engaged in detecting potential fraud within multinational corporations in Sub-Saharan Africa should possess.To achieve this goal,a quantitative approach ...The aim of this study is to examine the qualities that auditors engaged in detecting potential fraud within multinational corporations in Sub-Saharan Africa should possess.To achieve this goal,a quantitative approach was used to develop and test a research model based on three theories:agency theory,attribution theory,and cognitive dissonance theory.Responses from a panel of two hundred and nine(209)auditors who conducted a legal audit mission in a Sub-Saharan multinational were analyzed using SmartPLS 3.3.3 software.The results emphasize the crucial importance of auditors’competence and continuous training in fraud detection.However,professional skepticism and time pressure were found to be non-significant in this context.This conclusion provides essential insights for auditors,highlighting the key qualities needed to effectively address fraud detection within multinational corporations in Sub-Saharan Africa.展开更多
This paper focuses on the innovation of audit business management in the information technology era.In the wave of digitalization,audit companies need to adjust their management mode to take advantage of the advantage...This paper focuses on the innovation of audit business management in the information technology era.In the wave of digitalization,audit companies need to adjust their management mode to take advantage of the advantages of informatization.The key is to use digital tools to strengthen data analysis and reshape the audit process.This not only improves efficiency and accuracy but also improves the overall audit quality.The article also highlights the importance of developing a culture of continued auditor learning and skills development to ensure competitiveness in the digital age.At the end of the paper,the success of audit companies depends on innovation ability and the importance of combining management mode with technological innovation.展开更多
As China strives towards the second centenary goal,increasing attention is being paid to environmental pollution and other related issues.Concurrently,with the rapid development of big data technology,many big data so...As China strives towards the second centenary goal,increasing attention is being paid to environmental pollution and other related issues.Concurrently,with the rapid development of big data technology,many big data solutions have been applied to environmental pollution control audits,exerting a significant impact.This paper presents the current situation of environmental pollution audits,summarizing the application of big data from the perspectives of both domestic and international research.In terms of data collection and data analysis for environmental pollution audits,cloud platform technology,and visualization technology are selected based on multiple data sources.The impact in the field of environmental pollution control audits is further analyzed.It is found that the environmental pollution audit cloud platform is not yet perfect,the technical skills of audit personnel are insufficient,and some technologies are not mature.Relevant suggestions are put forward to provide a reference for the future development of big data technology and its integration with environmental pollution control audits.展开更多
A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objective...A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.展开更多
In this paper,we focus on providing data provenance auditing schemes for distributed denial of service(DDoS)defense in intelligent internet of things(IoT).To achieve effective DDoS defense,we introduce a two-layer col...In this paper,we focus on providing data provenance auditing schemes for distributed denial of service(DDoS)defense in intelligent internet of things(IoT).To achieve effective DDoS defense,we introduce a two-layer collaborative blockchain framework to support data auditing.Specifically,using data scattered among intelligent IoT devices,switch gateways self-assemble a layer of blockchain in the local autonomous system(AS),and the main chain with controller participation can be aggregated by its associated layer of blocks once a cycle,to obtain a global security model.To optimize the processing delay of the security model,we propose a process of data pre-validation with the goal of ensuring data consistency while satisfying overhead requirements.Since the flood of identity spoofing packets,it is difficult to solve the identity consistency of data with traditional detection methods,and accountability cannot be pursued afterwards.Thus,we proposed a Packet Traceback Telemetry(PTT)scheme,based on in-band telemetry,to solve the problem.Specifically,the PTT scheme is executed on the distributed switch side,the controller to schedule and select routing policies.Moreover,a tracing probabilistic optimization is embedded into the PTT scheme to accelerate path reconstruction and save device resources.Simulation results show that the PTT scheme can reconstruct address spoofing packet forward path,reduce the resource consumption compared with existing tracing scheme.Data tracing audit method has fine-grained detection and feasible performance.展开更多
A broad range of companies around the world has welcomed artificial intelligence(AI)technology in daily practices because it provides decision-makers with comprehensive and intuitive messages about their operations an...A broad range of companies around the world has welcomed artificial intelligence(AI)technology in daily practices because it provides decision-makers with comprehensive and intuitive messages about their operations and assists them in formulating appropriate strategies without any hysteresis.This research identifies the essential components of AI applications under an internal audit framework and provides an appropriate direction of strategies,which relate to setting up a priority on alternatives with multiple dimensions/criteria involvement that need to further consider the interconnected and intertwined relationships among them so as to reach a suitable judgment.To obtain this goal and inspired by a model ensemble,we introduce an innovative fuzzy multiple rule-based decision making framework that integrates soft computing,fuzzy set theory,and a multi-attribute decision making algorithm.The results display that the order of priority in improvement—(A)AI application strategy,(B)AI governance,(D)the human factor,and(C)data infrastructure and data quality—is based on the magnitude of their impact.This dynamically enhances the implementation of an AI-driven internal audit framework as well as responds to the strong rise of the big data environment.Highlights Artificial intelligence(AI)promotes the sustainability development of audit tasks.A fuzzy MRDM model extracts key factors from large amounts of data.Fuzzy decision-making trial and evaluation laboratory analysis accounts for dependence and feedback among factors.An effective framework of AI-driven business audit is proposed in which“AI cognition of senior executives”is the most important criterion.展开更多
This study assesses the implementation of energy conservation opportunities in four-star and five-star hotels in Nairobi. The Covid-19 pandemic had a significant impact on the Hospitality Industry. Currently, there is...This study assesses the implementation of energy conservation opportunities in four-star and five-star hotels in Nairobi. The Covid-19 pandemic had a significant impact on the Hospitality Industry. Currently, there is a growing inclination to furnish guests with superior and sustainable services in an energy-efficient and eco-friendly way. Comprehensive research was conducted from energy audits gathered from the establishments and contracted auditing companies, on top of this, hotel staff were given digital questionnaires. To add to the data, the researcher surveyed the hotels with engineering managers. The Energy Audits found that all 10 hotels had adopted Energy Conservation Opportunities (ECOs). After further analysis, the mean adoption rate of Energy Conservation Opportunities (ECOs) during the past three years was 55.83%, which was below the aim of 100%. According to studies, hotel staff manages energy to cut costs. The researcher found that hotels use up a lot of energy. However, they have conservation potential, depending on government policies, costs, ease of implementation, and management commitment to sustainable practices. Essentially, Energy Conservation Opportunities (ECOs) reduce energy expenditures and boost reliable revenues, especially during high energy prices and uncertainty.展开更多
This study aims to investigate the influence of emerging technology adoption on tax compliance, encompassing both the Internal Revenue Service’s (IRS) compliance audits and taxpayers’ compliance performance (collect...This study aims to investigate the influence of emerging technology adoption on tax compliance, encompassing both the Internal Revenue Service’s (IRS) compliance audits and taxpayers’ compliance performance (collectively, tax compliance). We employed the Gradient Descent optimization algorithm, an artificial intelligence (AI) technology application, to scrutinize the connection between the quality of US tax filings and the development of emerging technology, among other contributing factors. Additionally, we utilized multiple linear regression to evaluate the relationships between dependent variables, specifically IRS audit rates and the no-change rate at different income levels,1 and several independent variables, including a proxy for emerging technology in the form of tax software. Our findings reveal that while emerging technology significantly impacts tax compliance within the IRS and taxpayers’ performance, its effects vary across income groups. Notably, emerging technology seems to confer greater advantages to higher-income individuals compared to their lower-income counterparts. These study results hold considerable policy implications for government decision-makers in promoting the adoption of emerging technology among lower-income taxpayers.展开更多
As a crucial supervisory department overseeing economic operations,the audit department plays a pivotal role in safeguarding the healthy development of the country’s economy,exposing corruption,and effectively mainta...As a crucial supervisory department overseeing economic operations,the audit department plays a pivotal role in safeguarding the healthy development of the country’s economy,exposing corruption,and effectively maintaining social and economic peace and stability.The work of auditing involves detecting existing issues,providing remedies,and consistently contributing to national governance.However,as the market economic environment undergoes continuous changes,legal systems advance,and the audit environment becomes more complex,audit risks have gradually gained prominence.The prevention of audit risks has increasingly captured the attention of audit agencies at all levels.This necessitates audit institutions to continually adapt to new challenges,comprehend risks,and exert effective control over them.This article delves into the causes of audit risks,exploring ways to effectively identify and respond to these risks within a complex and ever-changing environment.The objective is to ensure the objectivity and accuracy of audit reports,allowing the audit function to truly serve as an“immune”system,protecting public interests.展开更多
In the current economic landscape characterized by a decelerating domestic economy,rising investments,and an extended project construction timeline,power generation enterprises must enhance their internal audit effort...In the current economic landscape characterized by a decelerating domestic economy,rising investments,and an extended project construction timeline,power generation enterprises must enhance their internal audit efforts to sustain their competitive edge in business development.Addressing systemic shortcomings methodically and practically can enhance the internal audit effectiveness within electric power enterprises and contribute to the steady enhancement of their production and operation performance.展开更多
In the era of big data,the construction and implementation of a quality control audit system are particularly crucial.This article delves into the impact of big data technology on quality control auditing,establishes ...In the era of big data,the construction and implementation of a quality control audit system are particularly crucial.This article delves into the impact of big data technology on quality control auditing,establishes a quality control auditing system in the big data era,and elucidates the pathway to realizing this system.Through the application of big data technology to quality control audits,there is an enhancement in audit efficiency,the attainment of more accurate risk assessment,and the provision of robust support for the sustainable development of enterprises.展开更多
The process of converting audit findings into actionable improvement measures within an enterprise is pivotal for achieving the“value-added”objective of internal audits and fostering sustainable business development...The process of converting audit findings into actionable improvement measures within an enterprise is pivotal for achieving the“value-added”objective of internal audits and fostering sustainable business development.By elucidating the definition and significance of transforming internal audit results,this study underscores the imperative of applying and effectively converting these findings.Additionally,it seeks to streamline the value assessment framework for internal audit result transformation and delineates key factors that impede this transformation.Furthermore,this study explores strategies to bolster the closed-loop audit management system and outlines specific methods for enhancing the transformation of internal audit results within the enterprise,thereby contributing to its overall progress.展开更多
基金supported by the Key-Area Research and Development Program of Guangdong Province under Grant No.2020B0101090004the National Natural Science Foundation of China under Grant No.62072215,the Guangzhou Basic Research Plan City-School Joint Funding Project under Grant No.2024A03J0405+1 种基金the Guangzhou Basic and Applied Basic Research Foundation under Grant No.2024A04J3458the State Archives Administration Science and Technology Program Plan of China under Grant 2023-X-028.
文摘Federated learning is an important distributed model training technique in Internet of Things(IoT),in which participant selection is a key component that plays a role in improving training efficiency and model accuracy.This module enables a central server to select a subset of participants to performmodel training based on data and device information.By doing so,selected participants are rewarded and actively perform model training,while participants that are detrimental to training efficiency and model accuracy are excluded.However,in practice,participants may suspect that the central server may have miscalculated and thus not made the selection honestly.This lack of trustworthiness problem,which can demotivate participants,has received little attention.Another problem that has received little attention is the leakage of participants’private information during the selection process.We will therefore propose a federated learning framework with auditable participant selection.It supports smart contracts in selecting a set of suitable participants based on their training loss without compromising the privacy.Considering the possibility of malicious campaigning and impersonation of participants,the framework employs commitment schemes and zero-knowledge proofs to counteract these malicious behaviors.Finally,we analyze the security of the framework and conduct a series of experiments to demonstrate that the framework can effectively improve the efficiency of federated learning.
基金This research was supported by the Qinghai Provincial High-End Innovative and Entrepreneurial Talents Project.
文摘Currently,there is a growing trend among users to store their data in the cloud.However,the cloud is vulnerable to persistent data corruption risks arising from equipment failures and hacker attacks.Additionally,when users perform file operations,the semantic integrity of the data can be compromised.Ensuring both data integrity and semantic correctness has become a critical issue that requires attention.We introduce a pioneering solution called Sec-Auditor,the first of its kind with the ability to verify data integrity and semantic correctness simultaneously,while maintaining a constant communication cost independent of the audited data volume.Sec-Auditor also supports public auditing,enabling anyone with access to public information to conduct data audits.This feature makes Sec-Auditor highly adaptable to open data environments,such as the cloud.In Sec-Auditor,users are assigned specific rules that are utilized to verify the accuracy of data semantic.Furthermore,users are given the flexibility to update their own rules as needed.We conduct in-depth analyses of the correctness and security of Sec-Auditor.We also compare several important security attributes with existing schemes,demonstrating the superior properties of Sec-Auditor.Evaluation results demonstrate that even for time-consuming file upload operations,our solution is more efficient than the comparison one.
基金supported by the National Natural Science Foundation of China under Grants No.U1836115,No.61922045,No.61877034,No.61772280the Natural Science Foundation of Jiangsu Province under Grant No.BK20181408+2 种基金the Peng Cheng Laboratory Project of Guangdong Province PCL2018KP004the CICAEET fundthe PAPD fund.
文摘With the intelligentization of the Internet of Vehicles(lovs),Artificial Intelligence(Al)technology is becoming more and more essential,especially deep learning.Federated Deep Learning(FDL)is a novel distributed machine learning technology and is able to address the challenges like data security,privacy risks,and huge communication overheads from big raw data sets.However,FDL can only guarantee data security and privacy among multiple clients during data training.If the data sets stored locally in clients are corrupted,including being tampered with and lost,the training results of the FDL in intelligent IoVs must be negatively affected.In this paper,we are the first to design a secure data auditing protocol to guarantee the integrity and availability of data sets in FDL-empowered IoVs.Specifically,the cuckoo filter and Reed-Solomon codes are utilized to guarantee error tolerance,including efficient corrupted data locating and recovery.In addition,a novel data structure,Skip Hash Table(SHT)is designed to optimize data dynamics.Finally,we illustrate the security of the scheme with the Computational Diffie-Hellman(CDH)assumption on bilinear groups.Sufficient theoretical analyses and performance evaluations demonstrate the security and efficiency of our scheme for data sets in FDL-empowered IoVs.
文摘This paper aims to investigate the effect of the characteristics of the internal audit function(IAF)on earnings management(EM)for a sample of 27 Tunisian listed companies.The authors employed the Correlated Panels Corrected Standard Errors model to estimate the regression equation.The results showed that EM is negatively associated with internal audit effectiveness,frequency of audit committee meetings with Chief Audit Executives(CAEs),the partial outsourcing of internal audit,and the firm’s size.Moreover,the authors found a positive relationship between EM and the use of IAF as a training ground for management and the private sector.This study is important to academics,regulators,and policymakers in introducing new governance reforms to strengthen the IAF as an important internal governance mechanism to reduce earnings management practices in emerging countries.The results also provide useful information for investors to examine the effect of internal audit characteristics on earnings management.
文摘The aim of this study is to examine the qualities that auditors engaged in detecting potential fraud within multinational corporations in Sub-Saharan Africa should possess.To achieve this goal,a quantitative approach was used to develop and test a research model based on three theories:agency theory,attribution theory,and cognitive dissonance theory.Responses from a panel of two hundred and nine(209)auditors who conducted a legal audit mission in a Sub-Saharan multinational were analyzed using SmartPLS 3.3.3 software.The results emphasize the crucial importance of auditors’competence and continuous training in fraud detection.However,professional skepticism and time pressure were found to be non-significant in this context.This conclusion provides essential insights for auditors,highlighting the key qualities needed to effectively address fraud detection within multinational corporations in Sub-Saharan Africa.
文摘This paper focuses on the innovation of audit business management in the information technology era.In the wave of digitalization,audit companies need to adjust their management mode to take advantage of the advantages of informatization.The key is to use digital tools to strengthen data analysis and reshape the audit process.This not only improves efficiency and accuracy but also improves the overall audit quality.The article also highlights the importance of developing a culture of continued auditor learning and skills development to ensure competitiveness in the digital age.At the end of the paper,the success of audit companies depends on innovation ability and the importance of combining management mode with technological innovation.
文摘As China strives towards the second centenary goal,increasing attention is being paid to environmental pollution and other related issues.Concurrently,with the rapid development of big data technology,many big data solutions have been applied to environmental pollution control audits,exerting a significant impact.This paper presents the current situation of environmental pollution audits,summarizing the application of big data from the perspectives of both domestic and international research.In terms of data collection and data analysis for environmental pollution audits,cloud platform technology,and visualization technology are selected based on multiple data sources.The impact in the field of environmental pollution control audits is further analyzed.It is found that the environmental pollution audit cloud platform is not yet perfect,the technical skills of audit personnel are insufficient,and some technologies are not mature.Relevant suggestions are put forward to provide a reference for the future development of big data technology and its integration with environmental pollution control audits.
文摘A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.
基金supported by the Fundamental Research Funds under Grant 2021JBZD204 and 2022RC006in part by the National Natural Science Foundation of China under Grant 62201029in part by the China Postdoctoral Science Foundation under Grant Grant BX20220029 and 2022M710007.
文摘In this paper,we focus on providing data provenance auditing schemes for distributed denial of service(DDoS)defense in intelligent internet of things(IoT).To achieve effective DDoS defense,we introduce a two-layer collaborative blockchain framework to support data auditing.Specifically,using data scattered among intelligent IoT devices,switch gateways self-assemble a layer of blockchain in the local autonomous system(AS),and the main chain with controller participation can be aggregated by its associated layer of blocks once a cycle,to obtain a global security model.To optimize the processing delay of the security model,we propose a process of data pre-validation with the goal of ensuring data consistency while satisfying overhead requirements.Since the flood of identity spoofing packets,it is difficult to solve the identity consistency of data with traditional detection methods,and accountability cannot be pursued afterwards.Thus,we proposed a Packet Traceback Telemetry(PTT)scheme,based on in-band telemetry,to solve the problem.Specifically,the PTT scheme is executed on the distributed switch side,the controller to schedule and select routing policies.Moreover,a tracing probabilistic optimization is embedded into the PTT scheme to accelerate path reconstruction and save device resources.Simulation results show that the PTT scheme can reconstruct address spoofing packet forward path,reduce the resource consumption compared with existing tracing scheme.Data tracing audit method has fine-grained detection and feasible performance.
基金supporting this work under Contracts No.MOST 110-2410-H-034-011 and MOST 110-2410-H-034-009,and 13th five-year plan of philosophy and social sciences of Guangdong Province,under Grants No.GD18CLJ02 and Department of education of Guangdong Province,China,No.2020WTSCX139.
文摘A broad range of companies around the world has welcomed artificial intelligence(AI)technology in daily practices because it provides decision-makers with comprehensive and intuitive messages about their operations and assists them in formulating appropriate strategies without any hysteresis.This research identifies the essential components of AI applications under an internal audit framework and provides an appropriate direction of strategies,which relate to setting up a priority on alternatives with multiple dimensions/criteria involvement that need to further consider the interconnected and intertwined relationships among them so as to reach a suitable judgment.To obtain this goal and inspired by a model ensemble,we introduce an innovative fuzzy multiple rule-based decision making framework that integrates soft computing,fuzzy set theory,and a multi-attribute decision making algorithm.The results display that the order of priority in improvement—(A)AI application strategy,(B)AI governance,(D)the human factor,and(C)data infrastructure and data quality—is based on the magnitude of their impact.This dynamically enhances the implementation of an AI-driven internal audit framework as well as responds to the strong rise of the big data environment.Highlights Artificial intelligence(AI)promotes the sustainability development of audit tasks.A fuzzy MRDM model extracts key factors from large amounts of data.Fuzzy decision-making trial and evaluation laboratory analysis accounts for dependence and feedback among factors.An effective framework of AI-driven business audit is proposed in which“AI cognition of senior executives”is the most important criterion.
文摘This study assesses the implementation of energy conservation opportunities in four-star and five-star hotels in Nairobi. The Covid-19 pandemic had a significant impact on the Hospitality Industry. Currently, there is a growing inclination to furnish guests with superior and sustainable services in an energy-efficient and eco-friendly way. Comprehensive research was conducted from energy audits gathered from the establishments and contracted auditing companies, on top of this, hotel staff were given digital questionnaires. To add to the data, the researcher surveyed the hotels with engineering managers. The Energy Audits found that all 10 hotels had adopted Energy Conservation Opportunities (ECOs). After further analysis, the mean adoption rate of Energy Conservation Opportunities (ECOs) during the past three years was 55.83%, which was below the aim of 100%. According to studies, hotel staff manages energy to cut costs. The researcher found that hotels use up a lot of energy. However, they have conservation potential, depending on government policies, costs, ease of implementation, and management commitment to sustainable practices. Essentially, Energy Conservation Opportunities (ECOs) reduce energy expenditures and boost reliable revenues, especially during high energy prices and uncertainty.
基金Wesley Leeroy (International Baccalaureate Program, Richard Montgomery HS, Maryland, USA) for his research assistance in preparing data and coding Gradient Decent algorithm。
文摘This study aims to investigate the influence of emerging technology adoption on tax compliance, encompassing both the Internal Revenue Service’s (IRS) compliance audits and taxpayers’ compliance performance (collectively, tax compliance). We employed the Gradient Descent optimization algorithm, an artificial intelligence (AI) technology application, to scrutinize the connection between the quality of US tax filings and the development of emerging technology, among other contributing factors. Additionally, we utilized multiple linear regression to evaluate the relationships between dependent variables, specifically IRS audit rates and the no-change rate at different income levels,1 and several independent variables, including a proxy for emerging technology in the form of tax software. Our findings reveal that while emerging technology significantly impacts tax compliance within the IRS and taxpayers’ performance, its effects vary across income groups. Notably, emerging technology seems to confer greater advantages to higher-income individuals compared to their lower-income counterparts. These study results hold considerable policy implications for government decision-makers in promoting the adoption of emerging technology among lower-income taxpayers.
文摘As a crucial supervisory department overseeing economic operations,the audit department plays a pivotal role in safeguarding the healthy development of the country’s economy,exposing corruption,and effectively maintaining social and economic peace and stability.The work of auditing involves detecting existing issues,providing remedies,and consistently contributing to national governance.However,as the market economic environment undergoes continuous changes,legal systems advance,and the audit environment becomes more complex,audit risks have gradually gained prominence.The prevention of audit risks has increasingly captured the attention of audit agencies at all levels.This necessitates audit institutions to continually adapt to new challenges,comprehend risks,and exert effective control over them.This article delves into the causes of audit risks,exploring ways to effectively identify and respond to these risks within a complex and ever-changing environment.The objective is to ensure the objectivity and accuracy of audit reports,allowing the audit function to truly serve as an“immune”system,protecting public interests.
文摘In the current economic landscape characterized by a decelerating domestic economy,rising investments,and an extended project construction timeline,power generation enterprises must enhance their internal audit efforts to sustain their competitive edge in business development.Addressing systemic shortcomings methodically and practically can enhance the internal audit effectiveness within electric power enterprises and contribute to the steady enhancement of their production and operation performance.
文摘In the era of big data,the construction and implementation of a quality control audit system are particularly crucial.This article delves into the impact of big data technology on quality control auditing,establishes a quality control auditing system in the big data era,and elucidates the pathway to realizing this system.Through the application of big data technology to quality control audits,there is an enhancement in audit efficiency,the attainment of more accurate risk assessment,and the provision of robust support for the sustainable development of enterprises.
文摘The process of converting audit findings into actionable improvement measures within an enterprise is pivotal for achieving the“value-added”objective of internal audits and fostering sustainable business development.By elucidating the definition and significance of transforming internal audit results,this study underscores the imperative of applying and effectively converting these findings.Additionally,it seeks to streamline the value assessment framework for internal audit result transformation and delineates key factors that impede this transformation.Furthermore,this study explores strategies to bolster the closed-loop audit management system and outlines specific methods for enhancing the transformation of internal audit results within the enterprise,thereby contributing to its overall progress.