On Nov.4^(th), AQSIQ (General Administration of Quality Supervision,Inspection and Quarantine of the People' s Republic of China), SAC (Standardization Administrationof China), National Audit Office of China (CNAO...On Nov.4^(th), AQSIQ (General Administration of Quality Supervision,Inspection and Quarantine of the People' s Republic of China), SAC (Standardization Administrationof China), National Audit Office of China (CNAO), and National Ministry of Finance of China jointlyheld the conference press on the national standard of Information Technology--Data Interface ofAccounting Software (GB/T 19581-2004) in Beijing. The standard was approved and issued on Sept. 20,2004 by AQSIQ and SAC, and it would come into effect all over the whole nation from January 1^(st),2005. Pu Changcheng, Vice Director of AQSIQ, Shi Aizhong, Vice Director of CNAO, Li Zhonghai. amember of the Party Group of AQSIQ and Director of SAC, the other leaders of concerned departmentssuch as National Ministry of Finance, National Telegraphy Office, and etc. attended the ConferencePress and made speeches. They fully affirmed the important significance and the achievements onstandardization work of electronic government business, and also they set new demands on the workfor the future.展开更多
In Decentralized Machine Learning(DML)systems,system participants contribute their resources to assist others in developing machine learning solutions.Identifying malicious contributions in DML systems is challenging,...In Decentralized Machine Learning(DML)systems,system participants contribute their resources to assist others in developing machine learning solutions.Identifying malicious contributions in DML systems is challenging,which has led to the exploration of blockchain technology.Blockchain leverages its transparency and immutability to record the provenance and reliability of training data.However,storing massive datasets or implementing model evaluation processes on smart contracts incurs high computational costs.Additionally,current research on preventing malicious contributions in DML systems primarily focuses on protecting models from being exploited by workers who contribute incorrect or misleading data.However,less attention has been paid to the scenario where malicious requesters intentionally manipulate test data during evaluation to gain an unfair advantage.This paper proposes a transparent and accountable training data sharing method that securely shares data among potentially malicious system participants.First,we introduce a blockchain-based DML system architecture that supports secure training data sharing through the IPFS network.Second,we design a blockchain smart contract to transparently split training datasets into training and test datasets,respectively,without involving system participants.Under the system,transparent and accountable training data sharing can be achieved with attribute-based proxy re-encryption.We demonstrate the security analysis for the system,and conduct experiments on the Ethereum and IPFS platforms to show the feasibility and practicality of the system.展开更多
The rapid development of the digital economy,driven by artificial intelligence(AI),is profoundly transforming traditional accounting practices and business models.The emergence of innovative models such as“wisdom+acc...The rapid development of the digital economy,driven by artificial intelligence(AI),is profoundly transforming traditional accounting practices and business models.The emergence of innovative models such as“wisdom+accounting”and“wisdom+financial sharing”has opened new avenues for enhancing enterprise decision-making support systems.This paper delves into the application of AI technology in accounting,examining its practical implementation and associated challenges.To mitigate potential risks arising from technological advancements,enterprises should establish robust and efficient intelligent financial systems.Additionally,organizations should foster a mindset of change within their accounting teams,improve the application of management information systems,strengthen internal control mechanisms,and continuously upgrade intelligent accounting software.Financial managers must adapt to the evolving landscape and proactively adjust their career paths and development strategies.展开更多
文摘On Nov.4^(th), AQSIQ (General Administration of Quality Supervision,Inspection and Quarantine of the People' s Republic of China), SAC (Standardization Administrationof China), National Audit Office of China (CNAO), and National Ministry of Finance of China jointlyheld the conference press on the national standard of Information Technology--Data Interface ofAccounting Software (GB/T 19581-2004) in Beijing. The standard was approved and issued on Sept. 20,2004 by AQSIQ and SAC, and it would come into effect all over the whole nation from January 1^(st),2005. Pu Changcheng, Vice Director of AQSIQ, Shi Aizhong, Vice Director of CNAO, Li Zhonghai. amember of the Party Group of AQSIQ and Director of SAC, the other leaders of concerned departmentssuch as National Ministry of Finance, National Telegraphy Office, and etc. attended the ConferencePress and made speeches. They fully affirmed the important significance and the achievements onstandardization work of electronic government business, and also they set new demands on the workfor the future.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the Special R&D Zone Development Project(R&D)—Development of R&D Innovation Valley support program(2023-DD-RD-0152)supervised by the Innovation Foundation.It was also partially supported by the Ministry of Science and ICT(MSIT),Korea,under the Information Technology Research Center(ITRC)support program(IITP-2024-2020-0-01797)supervised by the Institute for Information&Communications Technology Planning&Evaluation(IITP).
文摘In Decentralized Machine Learning(DML)systems,system participants contribute their resources to assist others in developing machine learning solutions.Identifying malicious contributions in DML systems is challenging,which has led to the exploration of blockchain technology.Blockchain leverages its transparency and immutability to record the provenance and reliability of training data.However,storing massive datasets or implementing model evaluation processes on smart contracts incurs high computational costs.Additionally,current research on preventing malicious contributions in DML systems primarily focuses on protecting models from being exploited by workers who contribute incorrect or misleading data.However,less attention has been paid to the scenario where malicious requesters intentionally manipulate test data during evaluation to gain an unfair advantage.This paper proposes a transparent and accountable training data sharing method that securely shares data among potentially malicious system participants.First,we introduce a blockchain-based DML system architecture that supports secure training data sharing through the IPFS network.Second,we design a blockchain smart contract to transparently split training datasets into training and test datasets,respectively,without involving system participants.Under the system,transparent and accountable training data sharing can be achieved with attribute-based proxy re-encryption.We demonstrate the security analysis for the system,and conduct experiments on the Ethereum and IPFS platforms to show the feasibility and practicality of the system.
文摘The rapid development of the digital economy,driven by artificial intelligence(AI),is profoundly transforming traditional accounting practices and business models.The emergence of innovative models such as“wisdom+accounting”and“wisdom+financial sharing”has opened new avenues for enhancing enterprise decision-making support systems.This paper delves into the application of AI technology in accounting,examining its practical implementation and associated challenges.To mitigate potential risks arising from technological advancements,enterprises should establish robust and efficient intelligent financial systems.Additionally,organizations should foster a mindset of change within their accounting teams,improve the application of management information systems,strengthen internal control mechanisms,and continuously upgrade intelligent accounting software.Financial managers must adapt to the evolving landscape and proactively adjust their career paths and development strategies.
