Apparatus for performing privacy impact assessment using file allocation table information, and method applied to the same

Abstract

The present invention discloses an apparatus and method for performing a personal information impact assessment using file allocation table information. The apparatus for performing a personal information impact assessment using file allocation table information according to the present invention includes a memory and at least one processor, wherein the processor processes the output of an evaluation template corresponding to each personal information impact assessment item to a terminal screen by executing a program for personal information impact assessment, enables the user to input an evaluation result in response to a query of an execution item number disclosed in the evaluation template, and manages and processes an index file by mapping the item number of the evidence material regarding the evaluation basis and opinion that led to the evaluation result one-to-one with the execution item number.

Description

Technology Field

[0001] The present invention relates to an apparatus and method for performing a personal information impact assessment using file allocation table information, and more specifically, to an apparatus and method for performing a personal information impact assessment using file allocation table information that enables automated assessment by mapping evaluation items and evidentiary materials one-to-one through FAT (File Allocation Table)-based index management without a database. Background Technology

[0002] Generally, a Privacy Impact Assessment (PIA) is an institutional procedure conducted by organizations or institutions to identify potential risks of personal information infringement in advance and to establish protective measures during the process of collecting, storing, processing, and providing personal information. Based on national laws, this assessment is a mandatory statutory task required of public institutions and personal information processors exceeding a certain size; it involves a process of examining the purpose of collection, processing procedures, retention periods, and security measures based on hundreds of detailed evaluation criteria.

[0003] The conventional method of conducting personal information impact assessments primarily involved evaluation agencies or committee members manually responding to questions for each evaluation item in accordance with standard guidelines provided by the government, and separately collecting evidentiary materials such as captured images, log files, and system configuration screens based on each evaluation result to attach to the evaluation report. In this process, each committee member had to identify a unique number (e.g., 1.1.1, 1.2.1, etc.) for each evaluation item and individually save or insert the corresponding evidentiary files into the document; consequently, the evaluation process was not only complex and inefficient but also highly susceptible to human error.

[0004] In particular, conventional technology has primarily utilized relational database management systems (DBMS) to clearly manage the correspondence between each evaluation item and evidentiary data. Database tables are filled with evaluation item codes, evaluation results, evidentiary file paths, and personnel information, and the system is configured to allow administrators to search for or modify data for specific items through SQL queries. However, such database-based systems contain several inherent problems, as follows.

[0005] First, database systems require significant costs and technical personnel for installation and operation. For evaluation agencies or small businesses, practical application is difficult because they often lack the dedicated IT infrastructure and management staff to set up and maintain database servers. Building a DB system solely to manage evidentiary materials for personal information impact assessments results in economic inefficiency and can lead to excessive resource waste depending on the project scale.

[0006] Second, since databases are structurally designed for storing structured data, it is difficult to efficiently manage unstructured data (e.g., captured images, document files, log data, etc.) handled in actual personal information impact assessments. Evaluators must manually input document file paths or image filenames, and if a file path changes, the database's referential integrity is easily compromised. Consequently, instances of missing or duplicated evidentiary files have frequently occurred.

[0007] Third, it is also pointed out as a problem that the hierarchical nature of the evaluation item system is not properly reflected in the database structure. Personal information impact assessment items are organized into a parent-child item structure and have sequential relationships in the form of, for example, 2.1.1, 2.1.2, and 2.1.3. However, it is difficult to explicitly express these hierarchical relationships in general database tables, and separate join operations or additional tables are required to identify the associations between items. This results in reduced efficiency for real-time searching and management by evaluators, and causes delays in the report generation process.

[0008] Fourth, existing systems do not adequately support version control or recency verification functions for evidential materials. Although evidential materials for the same item are frequently modified multiple times during the evaluation period, DB systems cannot automatically manage change history by file version, making it difficult to identify the latest evidential materials. This can lead to errors, such as the submission of inconsistent materials among evaluation committee members or the inclusion of past versions of evidential materials in reports.

[0009] Fifth, a major problem is that the low level of automation in the evaluation process leads to significant discrepancies among evaluators. In conventional technology, evaluators must manually input evaluation opinions for each item and attach supporting materials; consequently, even when evaluating the same institution, the consistency of results often varies depending on the evaluator. Furthermore, since the file names, storage locations, and attachment formats of each supporting material are not standardized, it was virtually impossible to automatically complete or merge evaluation reports.

[0010] Finally, while most current personal information impact assessment systems operate on web-based platforms or cloud servers, security risks persist due to their reliance on external network environments. Evidential data transmitted to external servers is vulnerable to hacking or data leaks, and there are limitations in that these systems cannot be used within an institution's closed network environment. Particularly for public institutions where security is critical, the inability to use internet-based database systems means that inefficient manual work involving local storage is still being repeated.

[0011] Ultimately, conventional methods for conducting personal information impact assessments suffer from problems where efficiency, consistency, and security are all compromised due to the complex linkage and management of evidentiary data for each assessment item and structural constraints centered on databases. Furthermore, the installation and maintenance costs of databases are excessively high for the sole purpose of systematically managing evidentiary data, and there are structural limitations that make it difficult to utilize them immediately within the practical working environments of assessment agencies.

[0012] Therefore, there is a growing need for a lightweight information management system that can intuitively and consistently manage evaluation items and evidential data without a separate database, and enable the generation of consistent reports by minimizing subjective intervention by evaluators. To address this challenge, a new approach is required that reflects the hierarchical structure of evaluation items while allowing for the direct mapping and tracking of evidential data at the file system level. Prior art literature

[0013] Korean Patent Publication No. 10-2873704 (Published on August 29, 2024) The problem to be solved

[0014] Accordingly, the present invention was created to solve the above-mentioned problems, and the objective of the present invention is to provide a device and method for performing a personal information impact assessment utilizing File Allocation Table (FAT) information, which maps each evaluation item and the corresponding evidentiary data one-to-one using a File Allocation Table (FAT) structure during the process of performing a personal information impact assessment, and enables systematic and consistent management of evaluation data without the need for a separate database.

[0015] Furthermore, the present invention provides an apparatus and method for performing a personal information impact assessment utilizing file allocation table information, which automatically generates a FAT-based hierarchical directory structure and classifies and stores evidential data in accordance with an evaluation item system, thereby reducing performance variance among evaluators and facilitating the automatic generation and verification of evaluation reports.

[0016] Furthermore, the invention provides a device and method for performing a personal information impact assessment using file allocation table information, which ensures the timeliness and consistency of data and simultaneously improves assessment quality and work efficiency by utilizing the metadata management function of FAT to manage information such as the path, modification history, and hash value of evidential data together.

[0017] The purpose of the invention is not limited to the purposes mentioned above, and other unmentioned purposes will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0018] A device for performing a personal information impact assessment using file allocation table information according to the first aspect of the present invention for achieving the above objective comprises a memory and at least one processor, wherein the processor processes the output of an evaluation template corresponding to each personal information impact assessment item to a terminal screen by executing a program for personal information impact assessment, enables the user to input an evaluation result in response to a query of an execution item number disclosed in the evaluation template, and manages and processes an index file by mapping the item number of the evidence material regarding the evaluation basis and opinion that led to the evaluation result one-to-one with the execution item number.

[0019] In addition, in the personal information impact assessment device utilizing the file allocation table information of the present invention, the processor can locate an evidence file stored in the hierarchical directory structure of the memory through an evidence search button activated in the evaluation template, and when capturing a page portion corresponding to the evidence among the found evidence files, identify the captured image as the evidence, and automatically assign an item number that maps one-to-one with the execution item number to the identified evidence, thereby processing it to be saved as the index file.

[0020] In addition, in the device for performing a personal information impact assessment utilizing the file allocation table information of the present invention, if there are multiple evidentiary materials for the execution items, they can be linked by one-to-one mapping with the execution item number, automatically derived and assigned as multiple item numbers, and then saved and processed as an index file.

[0021] In addition, in the device for performing a personal information impact assessment utilizing the file allocation table information of the present invention, evidence file location information indicating the location in the hierarchical directory structure of the evidence file can be generated, and the generated evidence file location information can be processed to be stored together with the storage location of the index file.

[0022] In addition, in the device for performing a personal information impact assessment utilizing the file allocation table information of the present invention, the index file can be stored and processed by including, as metadata, mapping information between the execution item number and the evidence material filename, path information of the evidence material file, author information, and the last modified date, based on the file allocation table structure of the FAT (File Allocation Table) file system.

[0023] In addition, in the device for performing a personal information impact assessment using file allocation table information of the present invention, the processor can determine whether the evidentiary data is up to date based on the author information or modification date among the metadata of the index file, and control it to output an update notification if the up to date is low.

[0024] In addition, in the personal information impact assessment device utilizing the file allocation table information of the present invention, the processor can automatically generate a folder structure corresponding to the execution item number system of the evaluation template and control the automatic assignment of a file name including the execution item number when an evidence data file is stored within the folder structure.

[0025] In addition, in the device for performing a personal information impact assessment utilizing file allocation table information of the present invention, the processor can configure an interconnected structure between a parent item folder and a child item folder based on the hierarchical relationship of the execution item number, and control the interconnected structure to be managed in the form of a cluster chain within a FAT directory table.

[0026] In addition, in the device for performing a personal information impact assessment utilizing the file allocation table information of the present invention, the index file may include a hash value for the execution item number and the evidence data file, and may be configured to automatically identify and remove duplicate evidence data within the same item through the hash value.

[0027] In addition, in the personal information impact assessment device utilizing the file allocation table information of the present invention, the processor can generate an automatically completed document of a personal information impact assessment report based on the execution item number and evidence data mapping information included in the index file, and control the automatic insertion of the path or thumbnail image of the evidence data for each evaluation item within the report.

[0028] Furthermore, a method for performing a personal information impact assessment using file allocation table information according to a second aspect of the present invention for achieving the above objective comprises, in a personal information impact assessment execution device, the step of executing a personal information impact assessment program to output an evaluation template corresponding to each personal information impact assessment item to a terminal screen; the step of receiving an evaluation result from a user in response to a query of an execution item number included in the evaluation template; the step of selecting or generating evidence materials regarding the evaluation grounds and opinions that led to the evaluation result; the step of managing and processing an index file by mapping the item number assigned to the evidence materials one-to-one with the execution item number; and the step of storing and managing the index file according to a hierarchical directory system of a File Allocation Table (FAT) structure.

[0029] In addition, in the method for performing a personal information impact assessment using file allocation table information of the present invention, the step of selecting the evidence data may include the step of searching for a corresponding evidence data file within a FAT-based directory structure of memory through an evidence data search button in an evaluation template, capturing the corresponding page area of ​​the found evidence data file to identify it as the evidence data, and then automatically assigning an item number that maps one-to-one with the execution item number and processing it to be saved as the index file.

[0030] In addition, in the method for performing a personal information impact assessment using file allocation table information of the present invention, the index file includes path information, author information, last modified date, and hash value for the execution item number and evidence data file, and may further include a step of automatically identifying and removing duplicate evidence data within the same execution item through the hash value. Effects of the invention

[0031] Therefore, the present invention utilizes a FAT structure to directly map personal information impact assessment items and evidentiary materials without a database, thereby offering the advantage of efficiently managing assessment data at low cost without the need for a separate server or management personnel.

[0032] In addition, the present invention has the advantage of reducing work variance among evaluators and improving the quality and reliability of evaluation reports by enabling consistent storage and tracking of evidentiary materials through a hierarchical directory structure automatically generated according to the evaluation item system.

[0033] Furthermore, the present invention has the advantage of ensuring accuracy and consistency in the personal information impact assessment process by automatically verifying the recency of evidentiary data and identifying and removing duplicate data based on metadata (file path, author, modification date, hash value, etc.) of the FAT file system.

[0034] The effects of the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description in the claims. Brief explanation of the drawing

[0035] FIG. 1 is a configuration diagram showing a device for performing a personal information impact assessment according to an embodiment of the present invention. Figure 2 is an example diagram showing an example of the storage of the evaluation template and index file of Figure 1. And, FIG. 3 is a flowchart illustrating a method for performing a personal information impact assessment according to an embodiment of the present invention. Specific details for implementing the invention

[0036] The advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0037] Furthermore, the embodiments described herein will be explained with reference to cross-sectional views and / or schematic drawings, which are exemplary illustrations of the present invention. Accordingly, the form of the exemplary drawings may be modified due to manufacturing techniques and / or tolerances, etc. Additionally, in each drawing of the present invention, each component may be depicted slightly enlarged or reduced for convenience of explanation.

[0038] The apparatus and method for performing a personal information impact assessment utilizing file allocation table information of the present invention map each evaluation item and the corresponding evidentiary data one-to-one using a File Allocation Table (FAT) structure during the process of performing a personal information impact assessment, and are configured to enable systematic and consistent management of evaluation data without the need for a separate database.

[0039] FIG. 1 is a configuration diagram showing a device for performing a personal information impact assessment according to an embodiment of the present invention.

[0040] As illustrated in FIG. 1, the personal information impact assessment execution device (100) utilizing the file allocation table information of the present invention includes a memory (110) and at least one processor (120). The processor (120) processes the output of an evaluation template (A) corresponding to each personal information impact assessment item on a terminal screen by executing a program for personal information impact assessment, enables the user to input evaluation results in response to a query of the execution item number disclosed in the evaluation template (A), and manages and processes the item number of the evidence material regarding the evaluation basis and opinion that led to the evaluation result by mapping it one-to-one with the execution item number to manage it as an index file.

[0041] The memory (110) stores an evaluation template (A), an evidence file, an index file, evaluation history data, and directory structure information based on a File Allocation Table (FAT). The memory (110) can be configured as a non-volatile storage and can be implemented in the form of a local storage device (e.g., HDD, SSD) or network storage (NAS, Cloud Storage, etc.). Additionally, a directory structure for each evaluation item (e.g., “1.1.1”, “1.1.2”, “2.1.1”, etc.) is created based on the FAT file system, and the evidence file is designed to be stored under each directory. This structure utilizes the hierarchical file management function provided by the FAT directory table, thereby enabling the clear representation of the relationship between each evaluation item and the corresponding evidence file without a database.

[0042] Meanwhile, the processor (120) serves as the control unit of the device (100) and executes an evaluation execution program to control the user's evaluation input, evidence data registration, and index file creation process. The processor (120) can be subdivided into a configuration including a user interface processing unit (121), a FAT management unit (122), an index file creation unit (123), and a report automatic generation unit (124).

[0043] The user interface processing unit (121) outputs an evaluation template (A) to the terminal screen and enables the user to perform selection or descriptive input for each evaluation item's query. The results entered by the user are automatically saved according to the evaluation criteria, and if necessary, the corresponding file within the FAT-based directory can be searched through the evidence search button.

[0044] The FAT management unit (122) directly controls file allocation information within the FAT structure to manage one-to-one mapping information between evaluation item numbers and evidence data files. Specifically, it tracks the physical location of each evidence data file using the cluster chain of the FAT and maintains logical and physical consistency by designating the evaluation item number as a folder name within the directory table. For example, if the execution item number is “2.1.1”, a “ / 2.1.1 / ” folder is automatically created in the FAT directory, and evidence data files such as “2.1.1.1.jpg” and “2.1.1.2.pdf” are stored in the folder.

[0045] The index file generation unit (123) automatically generates an index file by collecting metadata such as the directory location, filename, author, modification date, and hash value of each file in the FAT structure. The index file performs the role of comprehensively managing mapping information between evaluation item numbers and evidence data files, and ensures the traceability and consistency of evidence data when writing a report after the evaluation is performed. In addition, since the index file is linked to the FAT structure and is automatically updated when the file path is changed or the filename is modified, referential integrity issues of the database can be prevented.

[0046] The automatic report generation unit (124) automatically retrieves evidence materials for each evaluation item based on the information in the index file and compiles the personal information impact assessment report. In the report, evaluation results for each evaluation item, evaluation grounds, paths or thumbnail images of attached evidence materials are automatically inserted, and if necessary, it can be converted into PDF or DOCX format and used as a document for submission to the Personal Information Protection Commission.

[0047] Additionally, the device (100) may include various expandable embodiments. For example, if multiple evidence materials exist for the same item during evaluation, the processor (120) may assign an automatically derived item number (e.g., 2.1.1.1, 2.1.1.2, etc.) based on the item number to manage each evidence material separately. Additionally, the FAT management unit (122) may perform the function of automatically identifying and removing duplicate registrations of the same evidence material by calculating the hash value of each evidence material file and storing it in an index file.

[0048] In another embodiment, by applying an exFAT or FAT32 extended file system instead of the FAT structure, it is possible to manage large files and evaluation data for long-term preservation. In this case, the FAT structure expands the cluster size and allocation unit, enabling stable management of evaluation data even in environments with a large number of evaluation items or large file sizes.

[0049] In addition, to enhance security, this device can protect the integrity of evidence files by adding an encryption module to the FAT file system. For example, by applying AES-based file encryption or a public-key-based signature mechanism, it determines whether evidence files have been altered and prevents data falsification or alteration when submitting evaluation reports.

[0050] Accordingly, the personal information impact assessment device of the present invention is configured to intuitively manage evidentiary data for each evaluation item based on a FAT structure without a database, maintain performance consistency among evaluators, and simultaneously improve evaluation efficiency and reliability.

[0051] Furthermore, its simple system structure makes it easy to install and operate in public institutions, corporations, or internal network environments, and it offers scalability that allows for future application to security certification evaluation frameworks such as ISMS, ISO-27001, and ISO-27701.

[0052] The processor (120) can be modularized into a user interface (UI) layer and a file system linkage layer. The UI layer displays each execution item number (e.g., “2.1.1”) on an evaluation template (A) and calls a navigation dialog to a FAT-based layer directory (e.g., “ / PIA / 2.1.1 / ”) when the ‘Find evidence’ button is activated. When the user selects one of multiple formats such as a document (PDF, DOCX), an image (PNG, JPG), or a log (TXT, CSV), the file system linkage layer captures a specific page / area of ​​the corresponding file (e.g., the 400×300 pixel area at the top left of page 12 of a PDF). The captured image is stored in a temporary buffer, and then automatically assigned an item number rule (“2.1.1.1.jpg”) and saved in the corresponding execution item folder. When saved, the index file records the execution item number, the assigned evidence item number, the original file path / filename, the time of creation of the capture, the capture coordinates, and the page, so that it can be traced later. Such “filenames including item numbers” and “folder-item number rules” perform the role of an index without a separate database.

[0053] Furthermore, if multiple traces are required for a single execution item, the system automatically assigns derived numbers, such as “2.1.1.1” for the first trace and “2.1.1.2” for subsequent traces. To prevent conflicts, the derived numbers follow a procedure (checking for the existence of trace files → assigning a number if they do not exist, and incrementing an internal counter like '.2', '.3', etc. if they do). The index file stores the sorting order and **dependency relationships (preceding / subsequent traces)** of derived items within the same execution item, enabling natural arrangement and the detection of omissions during automatic report generation. In this case, even if trace formats (images, documents, logs) are mixed within the same execution item folder, they are consistently managed using the MIME type field of the index record.

[0054] The location information for evidence files is generated using both absolute paths (e.g., “D:\PIA\2.1.1\2.1.1.1.jpg”) and relative paths (e.g., “ / 2.1.1 / 2.1.1.1.jpg”) and recorded in the index file. Additionally, by retrieving and storing the FAT directory entry along with the first cluster number, file size, and timestamp (creation / modification), the physical location (cluster chain) can be traced back even in the event of a path change. This location information serves as a key for report generation, evidence integrity review, and backup and recovery procedures.

[0055] The metadata schema of the index file can be provided, for example, as 'eval_code (execution item number), evidence_id (including derived item number), path_abs / path_rel, author (author), t_create / t_update (creation / modification time), mime_type, cluster_start / cluster_len, note (brief comment by the evaluator)', and the schema can be stored in lightweight formats such as CSV / JSON / TOML to enhance interoperability between tools. The advantage of FAT-based metadata management is that consistent evidence management is possible without a database on lightweight infrastructures such as local and shared drives.

[0056] In addition, the recency determination logic calculates whether an update is required by comparing the t_update field of the index file with a revision elapsed time threshold (e.g., 90 days) or a policy reference date (e.g., notice revision date). Update notifications can be implemented via template item badges (e.g., 'Update Required'), dashboard notifications, or email / messenger integration. Notifications can be routed by author or department, and upon completion of the update, the index is automatically updated to prevent the inclusion of outdated versions when generating reports.

[0057] The processor (120) parses the item system (1.1.1, 2.1.1 …) of the evaluation template and automatically generates a folder tree. The generation rules reflect the parent-child relationships exactly, and a synchronization task updates the folder structure when items are added or deleted. By forcing the execution item number to be prefixed to the filename when saving evidence, consistent sorting and searching are possible regardless of which tool accesses it from, such as Explorer, CLI, or script. The automatic generation and naming rules can be customized through configuration (e.g., prefix separator '_', insertion of date, etc.).

[0058] The linkage structure between parent and child item folders can be implemented by referencing the cluster chain of the FAT directory table. The parent folder (e.g., “ / 2.1 / ”) reflects the entries and chain information of child folders (“ / 2.1.1 / ”, “ / 2.1.2 / ”) in the index, and the index viewer supports continuous navigation (parent to child) in the tree UI. By utilizing this chain structure, the index is rapidly reconstructed even when there are file system-level changes such as folder moves or merges, allowing for swift report conversion even when the item system is reorganized.

[0059] Meanwhile, duplicate identification calculates a hash, such as SHA-256, for each individual evidence file; if multiple files with the same hash exist within the same execution item, they are marked as duplicates and removed. Hash calculation can be performed at the time of storage or as a batch job, and files are determined to be duplicates if they have the same content, even if the filenames and paths differ. If necessary, fuzzy duplicate detection (similar images, OCR text similarity) is added as an auxiliary function to control "nearly identical" evidence. The index includes hash, dedup_status, and primary_evidence_id fields, allowing for the selection of reference aggregation (linking based on a single reference) instead of deletion.

[0060] In other words, duplicate identification is performed by calculating a hash value to determine the integrity and duplication of individual evidence files, and if multiple identical hash values ​​exist within the same execution item, marking them as duplicates or merging them. The hash algorithm used is not limited to the simple SHA-256; newer hash families with stronger collision resistance, such as SHA-512, SHA-3 (Keccak), and SHAKE128 / 256, can be selectively applied. Furthermore, depending on system policy, security strength can be enhanced using Double Hashing or Kid Hash (HMAC) methods. The hash calculation time and algorithm version are recorded together in the index metadata, enabling history tracking even during subsequent algorithm replacement or re-verification processes.

[0061] In particular, in environments requiring long-term preservation and high reliability, such as government agencies, local governments, and public institutions, verification methods based on Post-Quantum Cryptography (PQC) can be applied to prepare for the potential collapse of existing cryptographic systems due to the future emergence of quantum computers. Specifically, this system can generate a Post-Quantum Digital Signature by utilizing one of the Lattice, Code, or Multivariate-based PQC signature algorithms on the hash value of an evidence file. For example, NIST-standardized CRYSTALS-Dilithium or Falcon algorithms can be used; these algorithms operate efficiently even in closed-network based systems because they offer faster signature verification speeds and smaller signature sizes compared to existing RSA or ECDSA.

[0062] This signature value is stored together in the “Security Authentication Information” entry of the index file. Subsequently, by verifying both the hash value and the signature value during the verification of evidence, it provides non-repudiation functionality that goes beyond simple forgery detection. The public key and verification key used for the signature are registered in a trusted repository managed by each institution, allowing the authenticity of the original and the creator to be clearly confirmed solely through signature verification, even during future verification of the legal validity of evidence or external audits.

[0063] In addition, when the evidence file itself must be encrypted for storage and transfer, a quantum-resistant key encapsulation mechanism (PQC Key Encapsulation Mechanism) can be applied. For example, by using a lattice-based KEM method, such as the CRYSTALS-Kyber algorithm—one of the NIST PQC standard candidates—the symmetric key (such as AES) protecting the evidence file can be encapsulated and stored in a manner secure against quantum attacks.

[0064] In this configuration, the encryption key generated for each evidence file or group is encapsulated using the recipient's (verification agency or higher-level evaluation system) public key, and the encapsulated cryptographic information is recorded together in the index's "Security Key Management Information" entry. Through this structure, even if evidence is backed up to an external repository or transferred between agencies, the data exists only in a quantum-safe encrypted form, enabling the implementation of a Zero-Trust-based long-term security preservation system.

[0065] The report automatic generation unit (124) of the processor (120) synthesizes documents using an index file as the primary data source, a template (e.g., government guide form), and a merge engine. Each evaluation item section may automatically insert 'evaluation results, summary of evaluation grounds, and evidence thumbnails / path hyperlinks'. Thumbnails are generated in a separate cache based on the principle of non-damage to the original, and hyperlinks use relative paths to enhance portability (prevention of incompatibility when moving folders). Output formats support PDF / DOCX / HTML, and a Traceability Matrix may be additionally generated to provide item-evidence-page coordinates in a table format for auditing and regulatory compliance. As disclosed in the attached materials, the basis and expected benefits of automatic generation are advantageous for expanded application to multiple evaluation systems such as PIA / ISMS / ISO-27k.

[0066] Figure 2 is an example diagram showing an example of the storage of the evaluation template and index file of Figure 1.

[0067] As illustrated in FIG. 2, in this embodiment, an evaluation template (A') is displayed on the terminal screen, and input widgets (selectable, descriptive, file selection, capture button, etc.) corresponding to each execution item number (e.g., “2.1.1”) are arranged so that the evaluator can sequentially enter evaluation results and grounds. When the evaluator executes “Save,” the processor first automatically creates a hierarchical folder (e.g., “ / PersonalInformation_ImpactAssessment / 2 / 2.1 / 2.1.1 / ”) reflecting the execution item number system under the root directory of the evaluation project (e.g., “ / PersonalInformation_ImpactAssessment / ”), and enters the corresponding folder path as metadata for the evaluation template (A'). At this time, the hierarchical relationship between upper and lower item folders is constructed by decomposing based on the delimiter of the execution item number, and traceability is guaranteed because the folder name and the item code of the index file remain the same.

[0068] Once input for the evaluation template (A') is complete, the processor generates and saves a report file (e.g., “2.1.1_Evaluation_Results_Report.pdf” or “2.1.1_Evaluation_Results_Report.docx”) containing a summary of the results for the relevant implementation item within the “ / Privacy_Impact_Assessment / 2 / 2.1 / 2.1.1 / ” folder. The report file may automatically include evaluation result values ​​(e.g., Compliant / Partially Compliant / Non-Compliant), detailed grounds, recommendations for improvement, references to relevant laws / guidelines, and a list of evidence associated with the implementation item. Additionally, a report summary (e.g., “2.1.1_summary.json”) is generated in parallel within the same folder to serve as a reference for merging during future automated report integration.

[0069] Evidential materials are managed under the execution item folder based on a parent folder named “Evidential Materials,” and numbered subfolders such as First Evidential Materials, Second Evidential Materials, etc., are automatically created (e.g., “ / 2.1.1 / Evidential Materials / 2.1.1.1 / ”, “ / 2.1.1 / Evidential Materials / 2.1.1.2 / ”, etc.). The First Evidential Materials folder stores the original files of the relevant evidence along with images generated by the evaluator using the capture function, and the filenames are prefixed with the execution item number and a derivative number (e.g., “2.1.1.1_SystemSettings_Capture.png”). Multiple captured images can be stored sequentially in the second evidence folder, and an automatically incrementing counter is assigned at the time of storage to apply rules such as “2.1.1.2_Capture_001.png”, “2.1.1.3_Capture_002.png”, and “2.1.1.n_Capture_00n.png”. At this time, unstructured data such as original documents (PDF, DOCX, XLSX, PPTX), logs (TXT, CSV), and configuration files (JSON, XML) are also stored in the same folder; the MIME type, creation / modification times, and hash values ​​of each file are recorded in an index file, enabling duplicate identification and integrity verification.

[0070] The index file is located in the root of the execution item folder (e.g., “ / 2.1.1 / ”) and is managed in a lightweight format (JSON, CSV, etc.). The records may include at least the execution item number (eval_code), evidence ID (evidence_id: 2.1.1.1, 2.1.1.2 …), relative / absolute path (path_rel / path_abs), file type (mime_type), page / coordinate information of the capture source, hash (hash), author (author), creation and modification times (t_create / t_update), and summary description (note). The processor (120) updates the index file at each save point and, if evidence with the same hash is re-registered, indicates a duplicate status or adds only a reference link to the existing evidence. Additionally, the schema version of the index file is managed so that compatibility with previous data can be maintained even when the template is revised, the item system is changed, or the report format is extended.

[0071] As an extensible configuration, the processor (120) allows folder structure, file names, and metadata rules to be customized according to institution-specific regulations in the project settings screen. For example, a policy can be selectively applied to include the item title in addition to the item number in the folder name (“ / 2.1.1_EncryptionKeyManagement / ”), or to automatically assign the creation date (YYYYMMDD) and author initials to the file name (“2.1.1.1_20251023_AB.png”). An option to include English in folder names and file names is provided to consider a multilingual environment, and rules for handling spaces and special characters can be unified for compatibility between Windows / Linux / macOS.

[0072] As an example of evidence capture, it supports selective capture of a portion of the screen, the entire window, or multiple monitors, allows adding annotations (masking, highlighting boxes, number tagging) immediately after capture, and provides an option to apply automatic blurring to areas containing sensitive information (name, resident registration number, phone number, etc.). Blurring rules and masking specifications are recorded in index metadata, making it possible to reproduce which transformations were applied during post-audit. Additionally, for large-volume evidence (video, long-duration capture), thumbnail images and low-resolution previews are generated in a separate cache to prevent performance degradation during report synthesis.

[0073] As an example of sorting and selective exposure of multiple evidence, the processor can assign priority tags (e.g., Required, Recommended, Reference) to evidence belonging to the same task and apply a policy during automatic report generation where only 'Required' evidence is placed in the main body and 'Recommended / Reference' evidence is placed in the appendix. Additionally, it provides a "Evidence Drawer" view to quickly scan images, documents, and logs registered under the same item in a preview and rearrange the exposure order via drag-and-drop if necessary. The changed order is reflected in the order field of the index file, ensuring that the same rendering results are reproduced among team members.

[0074] As an example of backup, recovery, and migration, the entire folder structure under the project root and index files can be compressed (archived) together and backed up to an external repository; since relative path-based links are maintained during migration to another machine, immediate resumption is possible. When merging existing scattered data into a new system, the “Migration Utility” parses past folder and file names based on rules, rearranges them into execution item codes, and generates index files in bulk. During this process, file name conflicts, duplicate hashes, and missing metadata are automatically reported, allowing operators to make corrections afterward.

[0075] As an example of extending security and integrity, a digital signature (institutional private key) is optionally generated along with a content hash (SHA-256) when each evidence file is stored, and the signature value is recorded in the index. At the report submission stage, the hash and signature values ​​included in the index are verified to automatically determine whether tampering or forgery has occurred, and the verification results are reflected in the "Trace Table" on the report cover or in the appendix. Additionally, Role-Based Access Control (RBAC) is applied to separate author, reviewer, and approver permissions, and a write protection flag is set on critical evidence folders to block unauthorized changes after approval. Considering a closed network environment, all functions operate offline, and policies can be configured to export only in the form of an encrypted archive when transferring files externally.

[0076] As an example of operational efficiency, it provides recency notifications and regulatory integration features. For instance, a “Renewal Required” badge is displayed on evidence that has exceeded a certain period based on the evaluation guide revision date or internal policy change date, and notifications are sent via the dashboard and email / messenger. Once the update is complete, the revision time and version of the index are automatically updated, and since only the latest data is reflected when reports are regenerated, the incorporation of outdated versions is prevented. Additionally, standard templates, logos, and cover forms for each organization are pre-registered and automatically combined for each project to ensure consistent report deliverables.

[0077] In summary, the example of FIG. 2 includes a series of operations leading to the automatic creation of a hierarchical folder that directly reflects the execution item numbering system, the automatic saving of result reports based on input values ​​of an evaluation template (A'), the assignment of derived numbers to evidential materials and their saving according to folder / file rules, the management of paths, metadata, and hashes through an index file, the identification of duplicates, the verification of integrity, the notification of recency, and the automatic synthesis of reports. This configuration provides scalability that enables the stable maintenance of a one-to-one mapping between evaluation items and evidential materials without a database, reduces deviations caused by the evaluator's subjectivity, and allows for the operation of evaluation data with high portability and reproducibility even in large-scale, multi-institutional environments.

[0078] And, FIG. 3 is a flowchart illustrating a method for performing a personal information impact assessment according to an embodiment of the present invention.

[0079] As illustrated in FIG. 3, the method for performing a personal information impact assessment using file allocation table information proceeds by executing a personal information impact assessment program in a personal information impact assessment execution device (100) and outputting an evaluation template corresponding to each personal information impact assessment item to a terminal screen (S100).

[0080] Afterwards, the user's evaluation result is received for the query of the execution item number included in the evaluation template (S102).

[0081] In step S102, evidence materials for the evaluation basis and opinion that led to the evaluation result are selected or generated (S104), and the item number assigned to the evidence materials is mapped one-to-one with the execution item number and managed as an index file (S106).

[0082] Then, index files are stored and managed according to a hierarchical directory system of the FAT (File Allocation Table) structure (S108).

[0083] The detailed description of steps S100 through S108 described above and the description of additional possible steps shall be in accordance with FIGS. 1 and FIGS. 2 and the description thereof.

[0084] Although embodiments of the present invention have been described above with reference to the attached drawings, those skilled in the art will understand that the present invention may be implemented in other specific forms without changing its technical concept or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. Industrial applicability

[0085] Furthermore, since the present invention aims to provide an apparatus and method for performing a personal information impact assessment utilizing File Allocation Table (FAT) information, which maps each evaluation item and its corresponding evidentiary data one-to-one using a File Allocation Table (FAT) structure during the process of performing the personal information impact assessment, thereby enabling systematic and consistent management of evaluation data without the need for a separate database, the invention is industrially applicable as it is not only sufficiently capable of commercialization or business but also clearly and practically implementable. Explanation of the symbols

[0086] 100 : Personal Information Impact Assessment Execution Device 110 : Memory 120 : Processor

Claims

Claim 1 The system includes memory; and at least one processor, wherein the processor processes the output of evaluation templates corresponding to each personal information impact assessment item to a terminal screen by executing a program for personal information impact assessment, enables the user to input evaluation results in response to a query of an execution item number disclosed in the evaluation template, and manages an index file by mapping the item number of the evidence data regarding the evaluation grounds and opinions that led to the evaluation result one-to-one with the execution item number, wherein the index file is created in a structure that manages the execution item number, the evaluation result, and the item number of the evidence data in mutual linkage, the memory is configured in a hierarchical directory structure based on a file allocation table, and is controlled so that the evidence data and the evaluation result are stored under the directory corresponding to the execution item number, the processor generates a hash value using a hash algorithm with secured collision resistance for the evidence data, and controls the identification of whether there is duplication of evidence data within the same execution item based on the generated hash value, and applies post-quantum cryptography to the hash value or the evidence data A device for performing a personal information impact assessment using file allocation table information that controls to ensure the integrity and non-repudiation characteristics of the evidence by performing cryptographic protection processing based on PQC. Claim 2 A device for performing a personal information impact assessment utilizing file allocation table information, wherein, in claim 1, the processor finds an evidence file stored in a hierarchical directory structure of the memory through an evidence search button activated in the evaluation template, and when a page portion corresponding to the evidence file among the found evidence files is captured, the captured image is identified as the evidence, and an item number that maps one-to-one with the execution item number is automatically assigned to the identified evidence and processed to be saved as the index file. Claim 3 A device for performing a personal information impact assessment utilizing file allocation table information, wherein, in the case of multiple evidentiary materials for the above-mentioned performance items, the data is linked by being mapped one-to-one with the above-mentioned performance item number, automatically derived and assigned to multiple item numbers, and then saved and processed as an index file. Claim 4 A device for performing a personal information impact assessment utilizing file allocation table information, wherein, in claim 2, it generates evidence file location information indicating the location of the evidence file in a hierarchical directory structure and processes the generated evidence file location information together with the storage location of the index file. Claim 5 In claim 4, the device for performing a personal information impact assessment utilizing file allocation table information, wherein the index file is based on the file allocation table structure of a FAT (File Allocation Table) file system and stores and processes the mapping information between the execution item number and the evidence material filename, the path information of the evidence material file, the author information, and the last modified date as metadata. Claim 6 In claim 5, the device for performing a personal information impact assessment utilizing file allocation table information, wherein the processor determines the current status of the evidentiary material based on the author information or modification date among the metadata of the index file, and controls the output of an update notification if the current status is low. Claim 7 In claim 4, the device for performing a personal information impact assessment utilizing file allocation table information configured to automatically identify and remove duplicate evidence data within the same item through the hash value, wherein the index file includes hash values ​​for the execution item number and the evidence data file. Claim 8 In claim 7, the processor is a personal information impact assessment execution device utilizing file allocation table information that generates an autocompleted document of a personal information impact assessment report based on execution item numbers and evidence material mapping information included in the index file, and controls the automatic insertion of the path or thumbnail image of the evidence material for each evaluation item within the report. Claim 9 A personal information impact assessment execution device, a step of executing a personal information impact assessment program to output evaluation templates corresponding to each personal information impact assessment item to a terminal screen; a step of receiving evaluation results from a user in response to a query of an execution item number included in the evaluation template; a step of selecting or generating evidentiary materials regarding the evaluation grounds and opinions that led to the evaluation results; a step of mapping the item number assigned to the evidentiary materials one-to-one with the execution item number, and creating and managing an index file in a structure that mutually links the execution item number, the evaluation result, and the item number of the evidentiary materials; and a step of storing and managing the index file according to a hierarchical directory system of a FAT (File Allocation Table) structure while ensuring that the evidentiary materials and the evaluation results are stored under a directory corresponding to the execution item number; a step of generating a hash value using a hash algorithm with secured collision resistance for the evidentiary materials, and identifying duplicate evidentiary materials within the same execution item based on the generated hash value. A method for performing a personal information impact assessment using file allocation table information, comprising the step of performing cryptographic protection processing based on Post-Quantum Cryptography (PQC) on the hash value or the evidence data to secure the integrity and non-repudiation characteristics of the evidence data. Claim 10 In claim 9, the step of selecting the evidence material comprises the step of searching for a corresponding evidence material file within a FAT-based directory structure in memory through an evidence material search button in an evaluation template, capturing the corresponding page area of ​​the found evidence material file to identify it as the evidence material, and then automatically assigning an item number mapped one-to-one with the execution item number and processing it to be saved as the index file, thereby performing a personal information impact assessment using file allocation table information. Claim 11 A method for performing a personal information impact assessment using file allocation table information, wherein, in claim 9 or 10, the index file includes path information, author information, last modified date, and hash value for the execution item number and evidence material file, and further includes the step of automatically identifying and removing duplicate evidence materials within the same execution item through the hash value.

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