CN-121984665-A - Intelligent workshop safety task scheduling method based on dynamic multiparty calculation

CN121984665ACN 121984665 ACN121984665 ACN 121984665ACN-121984665-A

Abstract

The embodiment of the invention discloses an intelligent workshop safety task scheduling method based on dynamic multiparty calculation. The method comprises the steps of utilizing a task distribution center to send an appointed task to a safe computing center, utilizing the safe computing center to generate task capacity authentication according to the appointed task and send the task capacity authentication to a production unit passing identity authentication, utilizing the production unit to generate index data according to the task capacity authentication and send the index data to the safe computing center, utilizing the safe computing center to generate a secret state capacity value according to the index data and send the secret state capacity value to a bidding module, utilizing the bidding module to generate true value reduction according to the secret state capacity value and send the true value reduction to the safe computing center, utilizing the safe computing center to generate bidding results according to the true value reduction and send the bidding results to the task distribution center, utilizing the task distribution center to select corresponding production units to enter appointed production links according to the bidding results, and enabling different production links to realize task transfer through a storage cabinet.

Inventors

YANG CHEN
Gong Congcheng
LAN SHULIN
ZHU LIEHUANG
LI JUNYI
XU ZEYU

Assignees

北京理工大学

Dates

Publication Date: 20260505
Application Date: 20251215

Claims (10)

1. An intelligent workshop safety task scheduling method based on dynamic multiparty calculation is characterized by comprising the following steps: a task distribution center is utilized to send a designated task to a security computing center; Generating task capacity authentication according to the appointed task by utilizing the secure computing center, and sending the task capacity authentication to a production unit passing identity authentication; Generating index data by using the production unit according to the task capacity authentication, and sending the index data to the safety computing center; Generating a secret state capacity value according to the index data by using the secure computing center, and sending the secret state capacity value to a bidding module; Generating a true value reduction according to the secret state capacity value by utilizing the bidding module, and transmitting the true value reduction to the secure computing center; Generating a bidding result by the safety computing center according to the true value reduction, and sending the bidding result to the task distribution center; Selecting a corresponding production unit to enter a designated production link according to the bidding result by using the task distribution center; Wherein, different production links realize task transfer through the storage cabinet.
2. The intelligent shop security task scheduling method based on dynamic multiparty computing according to claim 1, wherein, The sending the designated task to the secure computing center by using the task allocation center comprises the following steps: And sending the task request data packet of the client to the secure computing center by using the task distribution center, and carrying out designated task description on the secure computing center.
3. The intelligent shop security task scheduling method based on dynamic multiparty computing according to claim 2, wherein, The generating task capability authentication by the secure computing center according to the appointed task and sending the task capability authentication to a production unit passing identity authentication comprises the following steps: and sending corresponding indexes of the task capability authentication to a production unit passing identity authentication in a production link by utilizing the security computing center to perform capability authentication.
4. The intelligent shop security task scheduling method according to claim 3, wherein, The generating, by the production unit, index data according to the task ability authentication, and transmitting the index data to the secure computing center includes: Encrypting the index data using a modified Shamir's secret sharing algorithm; The improved Shamir's secret sharing algorithm includes: Dynamically adjusting a threshold and an adaptive generator polynomial according to the security threat level, the server load and the network condition, and generating a plurality of share data and corresponding promise data; the correctness of the encrypted multiple share data is ensured by using a verifiable secret sharing algorithm.
5. The intelligent shop security task scheduling method according to claim 4, wherein, The generating, by the secure computing center, a secret capability value according to the index data, and sending the secret capability value to a bidding module includes: And the index data are stored in a plurality of servers of the secure computing center in a scattered manner, and the respective data parts are commonly transmitted to the bidding module by utilizing each server through a secret sharing technology of the secure interaction module.
6. The intelligent shop security task scheduling method according to claim 5, wherein, The generating, by the bidding module, a true value reduction according to the secret capability value, and sending the true value reduction to the secure computing center includes: And carrying out secret state comparison by utilizing the bidding module according to the secret state capability value, selecting data meeting the standard according to a comparison result, and carrying out true value restoration on the data meeting the standard based on a safe multiparty computing algorithm of a SHAREMIND platform.
7. The intelligent shop security task scheduling method according to claim 6, wherein, The step of selecting the corresponding production unit to enter the appointed production link by using the task allocation center according to the bidding result comprises the following steps: And selecting production units meeting the requirements by using the task distribution center, and sending bidding results and production tasks to the corresponding production units through the safety calculation center.
8. The intelligent shop security task scheduling method according to claim 7, wherein, The selecting the production unit meeting the requirements by using the task allocation center and sending the bidding result and the production task to the corresponding production unit through the security calculation center comprises the following steps: the task distribution center is utilized to send the production task and the work distribution of the production unit to the safety calculation center; judging whether the current task is in an intermediate link or not by utilizing the safety computing center; And if the current task is in the middle link, the number of the storage cabinet of the processing middleware in the last link is sent to a safety calculation center.
9. The intelligent shop security task scheduling method based on dynamic multiparty computing according to claim 8, further comprising: the safety computing center is utilized to distribute the number of the storage cabinet of the processing middleware of the previous link to the production unit of the current link; taking out the processing intermediate piece of the previous link according to the number of the storage cabinet of the processing intermediate piece of the previous link by using the production unit; After the processing of the production unit of the current link is completed, a new number is randomly acquired through the storage cabinet, and the processing middleware of the current link is stored in the corresponding storage cabinet.
10. The intelligent shop security task scheduling method based on dynamic multiparty computing according to claim 9, further comprising: after all production units in the current link are processed, encrypting the corresponding production results and the corresponding numbers of the storage cabinets to obtain encrypted data, and sending the encrypted data to the security computation center; judging according to the data type of the encrypted data by utilizing the safety computing center; If the encrypted data is the intermediate data required by the next link, the encrypted data is reserved in the secure computing center; If the encrypted data is the production condition report or the abstract information, carrying out true value restoration on the encrypted data through a secret sharing technology, and sending the true value restoration to the task distribution center to wait for the task distribution and production instructions of the task distribution center.

Description

Intelligent workshop safety task scheduling method based on dynamic multiparty calculation Technical Field The invention relates to the technical field of intelligent workshop safety scheduling. And more particularly, to an intelligent workshop safety task scheduling method based on dynamic multiparty computation. Background Currently, traditional border network security models rely primarily on establishing trust relationships at network borders, and lack effective global security safeguards within the network. Existing intelligent warehouse and shop scheduling systems typically employ a central server for centralized processing and management of data. However, in complex network environments, this approach presents its limitations, particularly in the absence of effective encryption measures during data transmission and the problem of imperfect inter-device authentication management, which makes these systems prone to be targets for malicious access, and difficult to effectively address internal threats. Furthermore, when faced with large amounts of distributed data, conventional centralized architectures face significant challenges in terms of both efficiency and security. Aiming at the problem of data centralization and convergence in the traditional workshop scheduling method, the prior art provides a novel lifting tree system architecture, aims at providing privacy protection without performance loss, and particularly pays attention to longitudinal safety. The framework theoretically demonstrates that it can achieve the same level of accuracy as a privacy-free approach, which provides powerful support for data privacy protection in an intelligent manufacturing environment. Regarding the encryption problem of sensitive data in the transmission process, an efficient and strong privacy-preserving real-phase discovery scheme is developed, and the security and privacy of the real-phase discovery process are ensured by representing tasks and perceived data of users by using a randomization matrix and designing a key derivation and encryption mechanism. The method solves the problem of protecting individual privacy in the data processing process of multiparty participation, and improves the safety of data sharing and collaboration. Aiming at a workshop scheduling data sharing and calculating cooperation scene among organizations, a novel safe calculation framework is provided by combining a federal learning technology and a blockchain technology. The framework utilizes the non-tamperability of the blockchain to enhance the trust relationship among multiple parties, and uses IPFS as a storage layer to reduce the coupling degree of the system, thereby improving the traceability and the robustness of the whole system. For communication and data security of large-scale distributed networks such as discrete workshops and supply chain management, a defense system architecture combining active and passive security is provided so as to adapt to the constantly changing security threat under the complex network environment. The system can cooperate with the capability of equipment of each manufacturer to quickly respond to various attack conditions, and an effective protection strategy is formulated and executed. In addition, a network security situation awareness model and characteristics thereof are further discussed, and a network security situation awareness platform model is designed by collecting and analyzing network transmission data, running states, attack information and the like so as to predict the development trend of network security. The existing research has been successful in solving the problems of data concentration, multiparty security calculation, communication security and the like, but does not solve the internal security problem caused by the traditional boundary network trust model, is not completely suitable for the design of a dynamic workshop task allocation and scheduling security architecture, lacks the cross-region and multi-network discrete distribution of workshops, has complex circulation of production links and intermediate parts, is difficult in safe interaction of different workshops and equipment types, has scattered data storage, needs data sharing and cooperation between different workshops and production units, and needs comprehensive consideration for protecting the respective privacy and sensitive information and the like. In addition, the number of the workshop internet of things platform equipment is huge and various, efficient equipment management and identity authentication mechanism access management are needed, and once the permission is granted in the traditional static access control mode, continuous evaluation is not carried out, so that the design of a reliable task allocation scheduling framework suitable for a dynamic production workshop is still a serious challenge. In the process of scheduling production tasks in an intelligent manufacturing shop, some potential