A Study on the Reconstruction of Audit Reporting Model of Risk-Oriented Auditing During Post-Financial Crisis Era

The audit profession field is the dominant force to push forward every revision of audit reporting model during many significant revisions before the beginning of the 21 st century, and they have a prominent tendency to protect auditing industry instead of a response to the users＇ information demand for investment decision. Traditional audit reporting model cannot satisfy the need of modem auditing, and it is essential to reconstruct current audit reporting model of modem risk-oriented auditing （MRA） during the post-financial crisis era, because it lacks communication value, valuable information, and effective alert information. The study provides the main contents about the reconstruction plan of the Public Company Accounting Oversight Board （PCAOB）： auditor＇s discussion and analysis （AD＆A）, required and expanded use of emphasis paragraphs in the auditor＇s report, auditor assurance on other information outside the financial statements, and clarification of language in the standard auditor＇s report. Then, the study discusses the effects of the reconstruction of audit reporting model on different stakeholders of audit including the auditors, the investors, the regulators, and the researchers.

Assessment of Appropriateness of Diagnostic Lymph Node Tissue Collection from the Operating Theater and by Interventional Radiologist. A Clinical Audit

Background: Appropriate sample requesting, collecting and timely dispatch to the appropriate laboratory is essential in establishing diagnosis of pathologies with lesions. Much time and effort may be wasted if this is not done according to certain standards. We conducted this study to assess the route of lymph node samples from requests to reaching the laboratories. Methods: We conducted an audit over a period from 4th June until 10th Aug 2023. Data for all the procedures performed over this period on lymph node samples (was entered into and analysed using Excel. Results: A total of eighteen samples for sixteen patients were obtained during this period. Median age of the patients was 34 years (19 - 73) with a M:F ratio of 5:11. Among the IR samples, nine samples were from the neck, three from inguinal area and one from axilla. Seven samples (53.8%) were tru-cut biopsies, six samples (46.15%) were FNA. All samples were sent to the pathology laboratory fixed in formalin. Samples for TB were sent only for five cases (31.25%) and for only two cases (12.5%) were samples sent for bacterial culture. For the OR samples, none were sent for either bacterial culture or TB. Overall, eight patients (50%) were not investigated for any infectious etiologies like brucella, toxoplasmosis, CMV, EBV plus other possible causes. Repeat sampling was required for 25% of patients (within and out of the audit period). Conclusions: to avoid delays in making diagnoses, it is paramount to consider infectious etiologies as possible diagnosis for lymphadenopathy and request appropriate investigations. This requires liaising with infectious diseases/clinical microbiology experts to guide regarding types of samples, types of media and timely dispatch to the correct laboratory.

A Federated Learning Framework with Blockchain-Based Auditable Participant Selection

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.

Sec-Auditor:A Blockchain-Based Data Auditing Solution for Ensuring Integrity and Semantic Correctness

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.

SHT-based public auditing protocol with error tolerance in FDL-empowered IoVs

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.

Impact of an official accountability audit on industrial structure adjustment:a case study of environmental regulation in China

As a unique environmental regulation in China,the official accountability audit was piloted in 2014.With a focus on prioritizing the ecological environment,officials in pilot districts have implemented economic construction,adjusted industrial structures,and promoted coordinated development between the economy and environment.The effects of implementation have garnered widespread attention from society.However,there is limited research on the impact of an accountability audit on industrial structure adjustments.Using the“Accountability Audit of Officials for Natural Resource Assets(Trial)”released in 2015 as a quasi-natural experiment,this study collected panel data from 279 cities between 2013 and 2017.It then empirically analyzed the impact mechanism and effects of the accountability audit on industrial structure adjustment using the Propensity Score Matching and Difference-in-Differences model.The research findings indicate that the accountability audit directly impacted industrial structure adjustment,promoting the upgrading of the primary industry to the secondary industry and restricting the development of the tertiary industry.In addition,the audit is beneficial for enterprise entry,but not conducive to technological innovation,and has no significant impact on foreign direct investment.This conclusion fills a gap in the existing research and provides valuable insights for policymakers.

Does the Internal Audit Function Play a Role in Mitigating Earnings Management?

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.

The Effects of Competence and Auditor Training on Fraud Detection Within Multinational Companies in Sub-Saharan Africa

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.

Innovation of Audit Business Management Models under the Conditions of Information Technology

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.

Analysis of the Impact of Big Data Technology on Environmental Pollution Control Audit

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.

Audit审核在车辆质检工作中的使用方法研析

Audit审核起源于德国大众,是企业模拟用户对自己的产品质量进行内部监督的觉行为。通过Audit审核在车辆质检工作中的应用,企业可以更加全面地了解车辆的质量状况,及时发现并解决问题,提升车辆的整体质量水平,从而满足消费者的需求,增强市场竞争力。Audit审核是站在用户的角度对成品车辆进行质量检查/测量的方法(内部和外部),获得汽车制造厂的广泛应用。Audit审核是在与用户相对的汽车制造厂里进行的审核检验,只有站在用户角度提升产品质量,才能发挥Audit审核的最佳作用。

Developing a GIS Audit Framework in the Context of Information Technology though a Reductive Model Approach

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.

Smart Contract Based DDoS Attack Traceability Audit Mechanism in Intelligent IoT

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.

Governance of artificial intelligence applications in a business audit via a fusion fuzzy multiple rule‑based decision‑making model

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.

Assessment of the Implementation of Energy Conservation Opportunities Arising from Energy Audits;A Study of Four-Star and Five-Star Hotels in Nairobi Kenya

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.

Linux下基于audit的文件操作溯源机制研究

随着网络通信技术的迅速发展,网络服务器系统相关安全研究越来越深入,如何溯源服务器系统中目标文件操作,成为文件系统安全的核心研究点。文章基于linux下audit系统,设计了一种文件操作溯源框架,分层解决文件操作监控、日志传输、暂存、提取、过滤、解析和存储,按需提取一定时间段内的一系列文件操作的核心日志数据信息,为服务器端文件安全提供溯源支持。

A Brief Discussion of Audit Risks and Their Causes

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.

An Uneven Impact of Emerging Technologies on Taxpayers With Various Income Levels Audited by the IRS: Empirical Evidence From an AI Technology Application and Regression Models

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.

隐性关联关系与审计费用——基于供应链工商大数据的研究

近年来,上市公司将其供应链商业关系隐藏化以规避信息披露要求的趋势越来越明显,不利于投资者评估和判断上市公司的交易性质和盈利能力。本文从审计师角度出发,以2010-2021年度我国A股上市公司为研究对象,基于供应链工商大数据度量隐性关联关系,分析隐性关联关系与审计费用之间的关系,结果发现上市公司与重要交易对象之间存在隐性关联关系提高了审计费用,一系列稳健性检验结果保持一致。在渠道检验中,研究发现隐性关联关系通过影响审计师投入,进一步影响审计费用。在分组检验中,研究发现隐性关联关系对审计费用的影响在高市场化进程地区、低信息透明度的公司以及当上市公司为事务所重要客户时更为显著。本文研究为审计师如何判断隐性关联关系问题提供了经验数据。

直面挑战:审计师数字化专长是否有助于提高审计质量?

借鉴审计师行业专长的度量方法,将数字化客户占比较高的审计师定义为数字化专长审计师,并检验在数字化变革过程中,积极参与数字化审计并取得数字化审计经验的审计师是否能够取得更好的审计结果。结果发现数字化审计专长审计师在数字化市场领域能够带来更优的审计质量,并且他们的特殊技能带来的积极作用能够被资本市场的投资者和分析师识别和认可(股价同步性更低且分析师预测更精准)。该结论为在数字化变革中,审计师如何能动应对大样本档案提供了证据,并为实务中事务所发展数字化审计提供了一些启示。