A SECURE LOCAL PROCESSING UNIT, STANDARD COMPARISON TASK-BASED, AND IRREVERSIBLE LEARNING CONTINUITY INDICATOR GENERATION SYSTEM.

Abstract

This invention relates to a system that generates a learner continuity token without sharing raw learner data. The system includes an enterprise end unit containing a processor, local memory, secure transaction area, user input unit, time measurement unit, local data storage unit, and communication unit; a standard comparison task package storage unit; a secure local transaction unit; a local data retrieval unit; a feature extraction unit; a unit for converting measurement values ​​to range classes; a one-way conversion unit; a learner continuity token generation unit; a token lifecycle unit; a temporal stability control unit; an inter-enterprise comparison unit; and a controllable transaction logging unit.Raw interaction data obtained from standard comparison tasks is processed on-premises without being transferred outside the on-premises, converted into a limited feature representation, separated into fixed-range representation values, and processed by a one-way transformation unit with at least one transformation parameter selected from among the on-premises key, period key, and session randomization value to create an intermediate representation that cannot be directly recovered from the raw interaction data. The learner continuity token generation unit generates a learner continuity token from this intermediate representation that does not contain any credentials or raw interaction data. Inter-premises comparison is performed using the learner continuity token or a comparison value derived from this token, without sharing raw data or credentials directly.

Description

SECURE LOCAL PROCESSING UNIT, ANCHOR TASK-BASED AND IRREVERSIBLE LEARNING CONTINUITY INDICATOR CREATION SYSTEM 1. TECHNICAL FIELD This invention relates to educational technologies, local data processing systems, and secure representation generation. Privacy-protected data transformation structures, cross-organizational learning continuity, and raw materials. This relates to authentication systems that operate without sharing user data. The invention is particularly useful in different educational institutions or different learning environments. Interaction data obtained from standard comparison tasks are processed securely locally. limited feature representation without transferring raw learner data outside the unit. transforming, converting this representation into an irreversible marker of learning continuity, and word a learner continuum that creates a subject marker that is renewable and can be canceled It relates to the token generation system. The invention also includes direct user identification, biometric data, raw response sequences, and raw time data. and without sharing personal data, only an irreversible token or token-derived information. Technical systems that perform inter-institutional continuity verification based on benchmark values. It includes. 2. STATE OF KNOWLEDGE OF THE ART In the field of educational technologies, tracking users across different systems and learning... various for the purpose of transferring the past and maintaining personalized learning processes Data processing systems are used. In these systems, user continuity is mostly ensured. User account, student number, email address, central identity provider, verifiable. through direct or indirect identity structures such as digital identity or learner wallet is provided. Systems that utilize behavioral profiling or behavioral signatures are also known. In these systems... the user's device usage, interaction style, response behavior, movement patterns, or By analyzing transaction habits, a user-specific behavioral representation is created. This 35 approaches aim to differentiate users based on their behavioral characteristics. However, this type of Behavioral representation in systems often involves user recognition or tracking. It is a permanent or semi-permanent profile serving the community. In document number 1 5 US20180034850A1, behavioral profiles are derived from user interactions. or the creation of a behavioral signature and the use of this representation to distinguish users or across devices. This document explains how behavioral signatures are used for association purposes. It forms a similar technique in terms of behavioral profiling. In contrast, the word The subject of the document is a comparison of standards applied in different educational institutions. irreversible, periodic tasks within the secure local processing unit. The creation of a renewable and cancelable learner continuity marker is not explained. Document US20160182657A1 describes user identification across multiple devices. This document describes the use of device-specific and behavioral features for this purpose. It forms a technically close relationship between behavioral characteristics and user association. However, this structure is not standardized without sharing raw learner data among educational institutions. Generates tokens on the device through comparison tasks and makes the token permanent. a system structure that uses a renewable continuity object instead of a behavioral profile It does not offer. Privacy-protected record matching systems are also known. In these systems, different data Records in the clusters are matched without sharing explicit identifying information. Research is being conducted in this field on encryption, hashing, Bloom's filter, and secure multilateral processes. Techniques such as calculation and the use of reliable tools are applied. However, this The approaches often involve comparing pre-existing record fields or records. It is based on establishing similarities between them. Document number WO2019040874A1 states that privacy-protected record matching is enabled. Methods for associating records without displaying text link data. This is explained in document US10430598B2, which describes a secure system based on the Bloom filter. The record matching structure is explained. These documents contain privacy-protected records. In terms of matching, they form a closely related technical framework. However, these solutions... Extracting local features from standard comparison tasks for learner continuity, measurement. Converting values ​​to range classes is not reversible with an institution or period key. the structure of generating a token and using this token as a renewable continuity object It does not explain. There are also various standards in the field of verifiable identity and learner qualification certificates. There are 35 of them. These structures contain data in the form of educational certificates, competencies, badges, or identification documents. It can be transmitted in a cryptographically verifiable manner. These approaches allow for a specific It aims to present information in a verifiable manner. However, these systems are raw learners. Generating an irreversible continuity marker on the device from interaction data and 2 5 inter-institutional matching architecture to be done solely through this token It does not explain. On-device data processing systems are also known. In these structures, model execution is performed locally. classification, on-device sample processing, or model access control are some of the techniques used. They are used. However, these solutions describe the general on-device processing architecture; Comparable standards comparison task protocol between educational institutions A specialized architecture for generating non-reversible and renewable learning continuity markers. It does not offer. Therefore, in the current state of the art; • Standard Comparison Task Package, • Raw data output of interaction data obtained from standard comparison tasks. a secure local processing unit that operates without exiting, • Local feature extraction, which transforms raw interaction data into a limited feature representation structure. unit, • a measurement that converts the representation of the feature in question into fixed-interval representation values. Unit for converting values ​​to range classes, • retrieve using institutional key, period key, or session randomization value Non-reversible learning continuity marker generating unit, • Token lifecycle, which governs the validity, renewal, and cancellation of the token. cycle unit, • and comparison values ​​between institutions that are solely based on a benchmark or a benchmark-derived benchmark. comparison unit working through • a technical learner continuity marker system that includes both with sufficient clarity It is not available. Therefore, learner matching can be done directly through behavioral signature or identity information. instead of doing that, within a secure local processing unit from standard comparison tasks through a generated, irreversible, renewable and cancelable continuity token A new technical solution is needed to achieve this. 3. THE PURPOSE OF THE INVENTION 35 The purpose of this invention is to facilitate the interaction of raw learners between different educational institutions or learning environments. an irreversible continuity marker that ensures continuity by learning without sharing data. The goal is to develop a creation system. 3 5 Another aim of the invention is to ensure learner interactions are not through free behavioral observation, Comparable via standard comparison task package and with limited technical input. The goal is to enable its transformation. Another aim of the invention is to obtain raw interaction data from standard comparison tasks. data remains securely within the local processing unit without leaving the device or organizational endpoint. The goal is to ensure that it is processed. Another purpose of the invention is to directly compare raw interaction data as an object of comparison. Instead of using this data, extracting a limited feature representation from it, and using those representation values The goal is to convert them into range classes and make them irreversible tokens. Another aim of the invention is to establish a persistent behavioral profile, such as a learner continuity marker. to prevent it from working, use periodic, institutional or session-based keys for the token. The goal is to create something renewable and potentially cancelable. Another purpose of the invention is to provide raw response sequences and raw time data for inter-institutional comparisons. User account, token only, without the transfer of biometric data or direct identification information. or to enable the use of a comparison value derived from the indicator. Another objective of the invention is to determine the stability of continuity markers generated at different times. By measuring its value, it provides temporal stability control instead of a one-time matching. The goal is to create a verification structure. 4. EXPLANATION OF THE FIGURES 4.1 No figures are included in the application. 5. EXPLANATION OF REFERENCES IN THE FIGURES 5.1 Since no figures are included in the application, a reference list is not provided. DETAILED DESCRIPTION OF THE 6TH INVENTION 6.1 General system structure 6.1.1 The invention is based on a standard comparison task with a secure local processing unit and back-end functionality. It relates to the system for generating irreversible learning continuity markers. 6.1.2 System; institutional endpoint, standard comparison task package storage unit, 35 secure local processing units, local data retrieval units, feature extraction units, measurement. Unit for converting values ​​to range classes, one-way conversion unit, learner continuity indicator production unit, indicator lifecycle unit, temporal stability 4 5 audit units, inter-agency comparison units and auditable transaction records It consists of units. 6.1.3 The system transfers raw interaction data belonging to the learner outside the organization's endpoint without It is in operation. 6.1.4 The system will be a standard comparison system to be applied in the same way across different educational institutions. It uses local interaction metrics derived from task packages. 6.1.5 The system uses raw interaction data directly as a comparison object. It does not use this data; it produces a limited feature representation from this data, and the said representation range converting them into classes and returning them after passing through a one-way conversion process. It creates an irreversible learning continuity marker. 6.1.6 The system provides raw response sequences, raw time data, and user data for inter-institutional comparisons. The account does not transfer student numbers, biometric data, or direct identification information. 6.1.7 Inter-institutional comparison, solely based on the learner continuity indicator or this This is done through a comparison value derived from the indicator. 6.2 Institutional endpoint 6.2.1 The institutional endpoint where standard comparison tasks are presented to the learner and locally It is the computer-based end device on which the processing steps are executed. 6.2.2 Enterprise terminal; processor, local memory, secure processing area, user input unit, It includes a time measurement unit, a local data storage unit, and a communication unit. 6.2.3 Institution end-unit, raw interaction arising from standard comparison tasks. transferring data to a secure local processing unit and preventing this data from going outside the corporate endpoint. It prevents it from coming out in its raw form. 6.2.4 The institution's end unit processes the raw materials generated during the standard comparison task implementation process. the data is stored in temporary memory only until the local feature extraction process is complete. It holds. 6.2.5 Raw interaction data is deleted after the local feature extraction process is complete. or is irreversibly summarized and converted to a summarized record state. 6.3 Standard Comparison Task Pack Storage Unit 35 6.3.1 Standard comparison task package storage unit, same technical support across different institutions local environment that stores standard comparison tasks used to create the input structure It is a data structure. 5 6.3.2 The standard comparison task is not for measuring the learner's level of knowledge, but for institutions standardized methods used to produce comparable interaction measures between them It's a short assignment. 6.3.3 Standard comparison task package; task ID, task sequence, task type, response The format includes a duration measurement area and a results recording area. 6.3.4 Task ID: Each standard comparison task is uniquely identified within the system. It causes them to separate. 6.3.5 Task sequence, the order in which standard comparison tasks are performed at the terminal. It specifies that it will be implemented. 6.3.6 Task types; sorting, matching, selection, short answer, task completion, and visual. It includes at least one pattern completion task. 6.3.7 Standard benchmarking task package, using the same task structure across organizations. It creates a technically comparable measurement range. 6.4 Secure local processing unit 6.4.1 Secure local processing unit, located within the enterprise endpoint and handling raw interaction It is a protected transaction structure that processes data without transferring it outside the organization. 6.4.2 Secure local processing unit; access control layer, temporary process memory, features subtraction executor, measurement value conversion to range classes executor, and single It includes a directional transformation executor. 6.4.3 The access control layer allows only authorized local processes to access raw interaction data. It enables access to the steps. 6.4.4 Temporary processing memory, raw interaction data obtained from standard comparison tasks. It keeps its measurements for a limited period of time. 6.4.5 The secure local processing unit retrieves the raw interaction data after the transaction is complete. It is structured in a way that will prevent its transfer outside the institution. 6.4.6 The secure local processing unit executes the necessary local processing steps for token generation. It is completed on the unit. 6.5 Local data receiving unit 35 6.5.1 Local data acquisition unit, during the execution of standard comparison tasks It is the unit that collects the interaction data generated on the organization's endpoint. 6 5 6.5.2 Local data retrieval unit; task start time, task end time, response selection time, number of corrections, task transition time, process completion time, and result status. It is taking measurements. 6.5.3 The local data collection unit collects the learner's name, surname, student number, contact information, and It does not directly collect identity data. 6.5.4 Measurements received by the local data acquisition unit are for feature extraction only. It is used as input data for the unit. 6.6 Feature extraction unit 6.6.1 Feature extraction unit, raw data obtained from standard comparison tasks. It is the local processing unit that converts interaction metrics into a limited feature representation. 6.6.2 Feature extraction unit; average response time, task transition delay, correction density, consistency rate, task completion rate, and error distribution values It calculates. 6.6.3 Feature extraction unit, identifier of the raw response sequence and individual response content. It is not used directly in its production. 6.6.4 Feature extraction unit, predefined for each standard comparison task. It generates feature fields. 6.6.5 Feature fields generated by the feature extraction unit are fixed-length features. It is being transformed into a series. 6.7 Unit for converting measurement values ​​to range classes 6.7.1 The unit for converting measurement values ​​to range classes is the feature extraction unit. fixed-range by separating the incoming numerical feature sequence into predefined interval classes. It is the unit that creates representational values. 6.7.2 Unit of conversion of measurement values ​​to range classes, response time, transition Features such as delay, correction density, and consistency ratio are predefined. It divides them into range classes. 6.7.3 As a result of the transformation process, each feature field has a limited number of representative values. It is being transformed into someone. 35 6.7.4 The unit for converting measurement values ​​to range classes is the raw measurement values. It prevents the exact reproduction of the token from within the token itself. 6.7.5 Feature array converted to December classes, one-way conversion unit is being transferred. 7 5 6.8 One-way conversion unit 6.8.1 The one-way conversion unit returns the feature array converted to range classes. converting the irreversible learner into an intermediate representation suitable for generating a continuity marker. It is a unit. 6.8.2 The one-way conversion unit converts the feature array into range classes for the institution. Transformation selected from a set of key, period key, and session randomization value. It operates in conjunction with the parameter. 6.8.3 One-way transformation results in raw interaction data, raw response sequence, or An intermediate representation is generated that prevents a return to singular duration measurement. 6.8.4 One-way conversion unit, different period key from the same raw interaction measurement. It enables the generation of different markers when used. 6.8.5 One-way conversion unit, in the form of a persistent behavioral profile of the token. It creates a transformation structure that restricts its use. 6.9 Learner continuity indicator production unit 6.9.1 The learner continuity indicator production unit receives the intermediate from the one-way transformation unit. It generates an irreversible learning continuity marker using representation. 6.9.2 Learner continuity marker; marker ID, period information, institution code, standard comparison task pack version, token expiration date, and token summary value It consists of. 6.9.3 Token hash value, feature array converted to range classes, and conversion. It is created by processing its parameters together. 6.9.4 The token does not contain direct identification information or raw interaction data. 6.9.5 The identifier is a technical representation object to be used for inter-institutional comparison. 6.10 Token lifecycle unit 6.10.1 Token lifecycle unit, validity of learner continuity token, It is the unit that manages renewal and cancellation processes. 6.10.2 Token lifecycle unit, validity start time for each token and It keeps track of the expiration date. 35 6.10.3 Tokens whose validity period has expired are not used in the comparison process. 6.10.4 When a new token is generated with a new period key, the previous token becomes inactive. is being received. 6.10.5 Canceled tokens are added to the cancellation list. 8 5 6.10.6 Inter-institutional comparison unit, indicators included in the cancellation list It excludes comparison. 6.11 Temporal stability control unit 6.11.1 Temporal stability control unit, learner continuity generated at different times. It is the unit that calculates the stability value of the indicators. 6.11.2 Temporal stability control unit, same standard comparison task package Representation proximity, feature space consistency, and periods among tokens belonging to the version. It calculates the exchange limit between them. 6.11.3 Temporal stability value based on multiple marker similarities instead of a single marker similarity This demonstrates marker consistency across the period. 6.11.4 Continuity when the stability value falls below the defined verification threshold This has not been verified. 6.11.5 Continuity verification when the stability value reaches the defined verification threshold. is being done. 6.12 Inter-institutional comparison unit 6.12.1 Inter-institutional comparison unit, learner continuity produced in different institutions. It is a communication structure that enables the comparison of signals. 6.12.2 Comparison unit, raw interaction data and direct credentials It does not transmit. 6.12.3 Comparison unit; token ID, token hash value, standard comparison The task pack version processes information such as validity and cancellation status. 6.12.4 The comparison unit produces a match score between two markers. 6.12.5 The match score is compared against a defined comparison threshold. 6.12.6 Inter-institutional continuity when the matching score falls below the comparison threshold No record is being created. 6.12.7 When the match score reaches the comparison threshold and the temporal stability value A continuity record is created when the verification threshold is reached. 35 6.13 Auditable transaction record unit 6.13.1 Auditable transaction record unit, token generation and comparison process It is the unit that stores the records of the technical processes that are generated. 9 5 6.13.2 Transaction log; endpoint ID, organization code, standard comparison task pack version, transaction time, token ID, transaction type, and transaction validation value It includes. 6.13.3 Transaction validation value, the previous transaction validation value and the new transaction record. It is the summary value created as a result of processing them together. 6.13.4 Auditable transaction log unit, raw interaction data and direct identification information It does not hide anything. 6.13.5 Auditable transaction record unit, token generation and comparison steps This allows for subsequent verification. 6.14 Working method 6.14.1 The institutional endpoint provides the learner with the standard comparison task package. 6.14.2 Local data acquisition unit, interaction occurring during standard comparison tasks. It is taking measurements. 6.14.3 Secure local processing unit, raw interaction metrics outside the enterprise endpoint. It operates without transferring data. 6.14.4 Feature extraction unit, limited feature representation from raw interaction measurements It constitutes. 6.14.5 Unit for converting measurement values ​​to range classes, limited feature representation It converts to fixed-range representation values. 6.14.6 One-way conversion unit, feature array converted to range classes It creates an irreversible intermediate representation by working together with the transformation parameter. 6.14.7 Learning continuity marker production unit, learning continuity from intermediate representation It produces the token. 6.14.8 Token lifecycle unit, validity and renewal of the generated token. It determines the situation. 6.14.9 The inter-institutional comparison unit compares raw indicators produced by different institutions. It compares data without sharing any information. 6.14.10 Temporal stability control unit, tokens generated at different times. It calculates the stability value between them. 35 6.14.11 When the matching score and temporal stability value reach the defined thresholds A continuity record is being created. 6.14.12 Auditable transaction record unit, relating to the token production and comparison process. It stores technical transaction records. 5.7. INDUSTRIAL APPLICABILITY The invention is based on a secure local processing unit, a standard comparison task, and a return process. Non-reversible learner continuity marker generation system; used in educational institutions. computer terminals, tablet-based learning devices, school information systems, learning It can be implemented on management systems and inter-institutional training data infrastructures. The organizational endpoint includes: processor, local memory, secure processing area, time measurement unit, and user. It is created using existing computer hardware, including an input unit and a communication unit. A secure local processing unit is a protected processing area reserved on the terminal processor, or It is implemented as a local processing layer with restricted access. The standard comparison task suite is stored in the local database or terminal memory. It is implemented as a maintained task package structure. Feature extraction unit, unit for converting measurement values ​​to range classes, unidirectional. conversion unit, token generation unit, token lifecycle unit, temporal stability audit unit and interagency comparison unit; running on the end-unit processor. It is implemented with local processing modules and network communication units. The system includes educational institutions, distance learning platforms, learning management systems, and exams. application endpoints, competency assessment systems, and inter-institutional student transfer It is used in the processes. With these features, the system in question utilizes existing computer hardware and a local database. infrastructure, secure transaction layer, network communication infrastructure, and training software systems. It is capable of being produced, installed, and implemented using these methods. 11

Claims

1. Secure local processing unit, standard comparison task-based and return It is a non-reversible learning continuity marker generation system; its feature is the processor. local memory, secure processing area, user input unit, time measurement unit, local Enterprise endpoint unit including data storage unit and communication unit, standard comparison Task package storage unit, secure local processing unit, local data retrieval unit, Feature extraction unit, unit for converting measurement values ​​to range classes, single directional transformation unit, learner continuity marker production unit, marker life cycle unit, temporal stability control unit, interagency comparison It includes a secure local transaction unit and an auditable transaction logging unit; Raw interaction data obtained from standard comparison tasks are used by the organization's endpoints. Processing on the corporate endpoint without transferring it outside the unit; feature extraction. The measurement unit produces a limited feature representation from raw interaction data; the limited feature representation of the unit that converts values ​​to range classes converting to fixed-interval representation values; the interval of the one-way conversion unit the representative values ​​converted into classes are institution key, term key and with at least one transformation parameter selected from among the session randomization values Intermediate representation that cannot be directly recovered from raw interaction data by processing them together. its creation; the learner continuity marker production unit from the aforementioned intermediate representation learner continuum that does not contain direct identity information and raw interaction data generating the indicator; the inter-institutional comparison unit performs the comparison using raw data. Continuity marker or marker-derived comparison that learns without sharing It is done based on its value.

2. The system for generating learner continuity markers according to Claim 1 is characterized by its institutional endpoint. standard comparison tasks of the unit are presented to the learner and local processing It is a computer-based end device on which the steps are executed.

3. The system for generating learner continuity markers according to claim 1 is a standard system. The task ID, task sequence, and task type of the 35 comparison task pack storage units, Standard comparison including response format, time measurement area and result recording area. It is about storing the task package. 12 5 4. It is a system for generating learner continuity markers according to claim 1, and its characteristic is; standard comparison task package between organizations based on the same task structure It should be structured in a way that creates a comparable measure of interaction.

5. The system for generating learning continuity markers according to claim 1 is characterized by its secure nature. local processing unit access control layer, temporary process memory, feature extraction executor, executor for converting measurement values ​​into range classes, and one-way It includes a transformation executor.

6. The system for generating learning continuity markers according to claim 1 has the following feature: local data. task start time, task end time, response selection time of the receiving unit, Number of corrections, task transition time, process completion time, and result status. It is about taking measurements.

7. The system for generating learning continuity markers according to claim 1 has the following characteristic: local data the receiving unit's name, surname, student number, contact information and direct information of the learner It does not collect identity fields and does not include these fields in token production.

8. The system for generating learner continuity markers according to claim 1 has the following characteristic: Average response time of extraction unit, task transition delay, correction density, consistency rate, task completion rate, and error distribution values It is a calculation.

9. According to claim 1, the learner is a continuity marker generation system and its characteristic is; characteristic Continuum that learns the raw response sequence and the individual response content of the subtraction unit It does not directly transfer the token into the code.

10. According to claim 1, the learner is a continuity marker generation system with the following characteristic: The subtraction unit has predefined characteristics for each standard comparison task. It generates feature fields and converts these feature fields into a fixed-length feature array. It is a conversion of 35.

11. The system for generating learner continuity markers according to claim 1 is characterized by its measurement feature. Response time of the unit converting values ​​to range classes, task transition 13 5 delay, correction intensity and consistency ratio fields are predefined. It is the process of dividing them into range classes.

12. According to claim 1, the system for generating learner continuity markers is characterized by its measurement feature. each feature field of the unit that converts values ​​into range classes has a limited number of features. converting one of the representative values ​​and the raw measurement values ​​directly from the indicator. It produces a representational structure that prevents its recovery.

13. According to claim 1, the learner continuity marker generation system is characterized by its unidirectional nature. the converted attribute array of the conversion unit into range classes institutional key It is the process of working together.

14. The system for generating learner continuity markers according to claim 1 is characterized by being one-way. the property sequence converted into range classes of the conversion unit period key It is the process of working together.

15. According to claim 1, the learner continuity marker generation system is characterized by its unidirectional nature. session of the feature array converted into range classes of the conversion unit It works together with the randomization value.

16. According to claim 1, the learner continuity marker generation system is characterized by its unidirectional nature. a different period key from the same raw interaction measurement of the conversion unit Its use enables the generation of different learner continuity markers.

17. According to claim 1, the learner continuity marker generation system's characteristic is; learner continuity indicator, indicator ID, period information, institution code, standard comparison task pack version, token expiration date, and token hash value It includes.

18. According to claim 1, the learner continuity marker generation system's characteristic is; marker Feature array and transformation of 35 summary values ​​into range classes. It is created by processing its parameters together. 14 5 19. According to claim 1, the learner continuity marker generation system's feature is; marker Validation start for each learner continuity marker of the life cycle unit It keeps track of the time and the expiration date.

20. According to claim 1, the learner's continuity marker generation system has the following characteristic: marker In the comparison process, the expired token of the life cycle unit It means rendering it unusable and passive.

21. According to claim 1, the learner's continuity marker generation system has the following characteristic: marker When a new token is generated with the new period key of the lifecycle unit, the previous one... It is the process of making the indicator passive.

22. According to claim 1, the learner continuity marker generation system has the following characteristic: marker The lifecycle unit writes the canceled tokens to the cancellation list and the institutions Indicators included in the cancellation list of the comparison unit are excluded from comparison. It is about letting go.

23. According to claim 1, the learner is a continuity marker generation system whose characteristic is; temporal stability control unit belongs to the same standard comparison task pack version. representational proximity, feature domain consistency, and inter-period consistency among markers. It is a calculation of the change limit.

24. According to claim 1, the learner is a continuity marker generation system whose characteristic is; temporal The stability value of the stability control unit is below the defined verification threshold. The problem is that it doesn't create continuity verification when left unchecked.

25. According to claim 1, the learner is a continuity marker generation system whose characteristic is; temporal the stability value of the stability control unit is determined to the specified verification threshold. It creates continuity verification when it reaches that point. 35 26. According to Claim 1, the system for creating learner continuity markers is characterized by its features; institutions the identifier of the comparison unit, the identifier hash value, the standard comparison task pack version, validity information, and cancellation status information. It processes the data and does not transmit raw interaction data. 5 27. According to Claim 1, the system for creating learner continuity markers is characterized by its features; institutions the matching score between two learner continuity markers of the inter-comparison unit The process involves generating a score and comparing that score against a predetermined benchmark.

28. According to Claim 1, the system for generating learner continuity markers is characterized by its ability to function within institutions. when the matching score of the comparison unit reaches the comparison threshold and Continuity log when temporal stability value reaches the verification threshold. It is the creation of.

29. It is a system for generating learner continuity markers according to Claim 1, and its characteristic is; The endpoint ID, institution code, and standard of the auditable transaction logging unit. comparison task pack version, transaction time, token ID, transaction type, and transaction It creates a transaction record containing a verification value.

30. According to claim 29, the learner's continuity marker generation system has the characteristic of; process the verification value is the previous transaction verification value combined with the new transaction record. It is a summary value generated as a result of processing.

31. It is a system for generating learner continuity markers according to Claim 1, and its characteristic is; raw interaction data and direct identification information of the auditable transaction log unit not keeping technical process records relating to token production processes It is to hide.

32. According to Claim 1, the system for generating learner continuity markers has the following characteristic: institutional endpoints. raw interaction data obtained from the unit's standard comparison tasks secure transaction area, local memory, time that operates without transferring data outside the corporate endpoint. measurement unit, standard comparison task package storage unit, local data retrieval unit, feature extraction unit, unit for converting measurement values ​​to range classes, It includes a one-way transformation unit and a learner continuity marker production unit. 35 33. According to claim 32, the system for creating a learner continuity marker is characterized by its institutional nature. the end unit stores the raw interaction data of the secure processing area in temporary process memory. It holds the raw interaction data and deletes it after the token generation is complete. or it is the process of bringing the record to an irreversibly summarized state. 16 5 34. According to Claim 32, it is a system for creating a learner continuity marker; its characteristic is; institution learner generated with the standard benchmark taskpack version of the end unit It is the act of recording the continuity marker together.

35. According to claim 32, the system for creating learner continuity markers is characterized by its institutional nature. During the token generation process of the end unit, the raw response sequence, raw duration data, User accounts, biometric data, and direct identity information are exchanged between institutions. It is the failure to transfer it to the comparison unit. 17