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.

基于“Classin+Audition”的校外“云”合唱教学实践探索

“云”合唱是信息技术迅猛发展下,“合唱+互联网”的音乐创作与传播新方式。电脑、耳机和摄像头机,或者更简便的智能手机,这些普通的家庭数字设备就可以支持学生参与“云”合唱的学习与实践。通过Classin平台与Audition音频编辑软件的功能,积极探索校外“云”合唱教学,满足了学生在线开展艺术实践的需求,应用数字化技术体验合作的快乐。

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.

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。

基于声卡和Adobe Audition的动弹性模量测试方法研究

弹性模量是表征材料弹性性质的特征物理量,在工程应用中具有重要的作用。设计了基于声卡和Adobe Audition的材料动弹性模量测定的测试系统,基于声卡的数据采集系统由传感器、调理装置、计算机组成。对不同长度的等强度悬臂梁进行实验,利用Matlab软件进行实验数据分析,得到悬臂梁的固有频率,从而根据理论公式计算出材料的动弹性模量,并与有限元分析结果进行比较。实验结果表明该测试系统测量精度较高,该试验方法简单易行,具有较强的实用性。

用Audition软件辅助测量弹簧振子的振动周期

介绍利用adobe audition 1.5软件测量弹簧振子的周期,研究周期与质量的关系。该方法能将测量值精确到0.001,从而提高实验精确度。

运用Adobe Audition打造多媒体课件中的完美声音

声音素材的处理是多媒体课件制作中的重要环节,高质量的音效能大大提高多媒体课件中的渲染力。对多媒体课件制作中声音的获取、加工处理等过程中存在的问题进行了探讨,并提出了解决的方法。

基于Audition与声卡的刚体转动惯量的测定

通过声卡并运用Audition软件可以对扭摆次数和时间进行自动记录和保存,计算出扭摆周期,从而测定刚体转动惯量.从图形上读出时间数据具有直观、快捷、准确的特点,减少了由于人为因素造成的误差.

Audition对音频的降噪处理

由于各种原因,录制的音频(无论语音还是歌唱)出现一定响度的噪声是经常发生的。当噪声太明显时就会影响听觉效果,降噪处理就是消除这种噪声的基本方法。阐述了采用Audition软件处理常见音频噪声的方法,简单实用。

基于Adobe Audition的张力测试探讨

介绍Adobe Audition的测频方法,借用frequency Analyze功能,对弦线张力的测试进行探讨,得出可行、简便,精确的结论。

Adobe Audition3.0音频素材制作应用技巧探究

随着时代的发展,在信息化的大背景下,多媒体技术在文化教育方面得到了广泛的应用。而音视频制作是多媒体技术的主要构成部分。该文基于Adobe Audition 3.0软件,具体阐述了降噪等音效处理技巧,对如何利用Audition来制作音频素材进行探讨研究。

任务驱动法在《音频处理(Audition)》课程中的应用

任务驱动法以解决问题、完成任务为主,是一种多维、互动式的教学方法。作为操作实践性很强的应用软件类课程,《音频处理(Audition)》适合使用任务驱动法教学。对高职高专这一层次的学生而言,基于任务驱动法的实训比单纯的课堂讲授更有效,更能激发学生的兴趣,真正做到"趣"生于课堂",乐"动于心灵。

利用Adobe Audition1.5测重力加速度

介绍了利用声学处理软件Adobe Audition1.5记录小球自由落体运动的时间,再通过直线运动公式计算重力加速度的方法.该方法可以将运动时间精确到0.001s,从而能够更精确地计算出重力加速度.

Adobe Audition在声波和拍实验中的仿真与优化

在计算机实测实验的基础上,采用Adobe Audition软件对声波和拍的实验过程和实验数据进行分析,测量两列波合振动的拍频和频率,并改进了传统实验方法。对比可知,改进的实验测量方法更直观、简便,测量结果也更准确。

基于Audition环境下的电声技术课程实践教学模式探讨

在电声技术课程的实践教学过程中,由于实验设备和环境条件等因素的制约,有些实验项目不具有可操作性,通过多媒体计算机和音频编辑软件模拟声学环境以及电声系统的系统硬件功能使得某些实验项目的得以实现。在实践教学过程中,采用课堂训练与课外实践相结合的实践教学模式,从而提高学生的动手能力以及综合运用知识的能力。