A method and system for transferring large files

Abstract

This invention provides a method and system for transferring large files. Each file within a large file is allocated to a corresponding file cluster according to its sensitivity level. Based on the sensitivity level of each file cluster, the cluster is divided into blocks. An independent encryption key is generated for each file block, and the file blocks are encrypted and transmitted to the receiving end. At the receiving end, an independent decryption key is generated for each encrypted file block, and all decrypted file blocks are merged to form the original file cluster. This invention divides large files into multiple file clusters based on sensitivity, dynamically blocks file clusters based on their sensitivity, and generates independent encryption and decryption keys for each file block, enhancing the security and tamper-proof capabilities of large file transmission. Furthermore, by extracting multi-level features from elements, element classes, and even the database level, a highly correlated hierarchical fingerprint chain is generated, enabling precise location and traceable verification of tampering.

Description

Technical Field

[0001] This invention relates to the field of secure transmission technology for large files, and more specifically, to a method and system for transmitting large files. Background Technology

[0002] As the construction of the monitoring network for the implementation of national spatial planning continues to advance, government departments at all levels, planning units, and monitoring agencies need to frequently exchange large files (usually larger than 1GB) containing sensitive spatial databases and attribute databases. These files carry important national spatial planning data, monitoring and evaluation results, and decision support information, which are of great significance to national security and economic and social development.

[0003] File transfer presents serious security challenges: sensitive data may be accessed without authorization during transmission, leading to data leakage; data may be maliciously tampered with during transfer, affecting its authenticity and reliability; traditional verification methods typically only check file integrity, making it difficult to accurately locate the tampering location and provide effective evidence of tampering; the overall encryption and decryption efficiency of large files is low, and when using fragmented encryption for transmission, a single key poses security risks, while multiple keys present complex management issues. Summary of the Invention

[0004] This invention addresses the technical problems existing in the prior art by providing a method and system for transmitting large files. It achieves encryption and anti-tampering of large files during transmission, thereby meeting the requirements for data confidentiality and integrity. It solves the need for secure transmission of large files in the national land spatial planning implementation monitoring network and improves the security, reliability and traceability of data transmission.

[0005] According to a first aspect of the present invention, a method for transferring large files is provided, comprising:

[0006] The system identifies and classifies large input files, and assigns each identified file to a corresponding file cluster based on its sensitivity level. Each file cluster has a corresponding sensitivity level.

[0007] For any file cluster, the file cluster is divided into blocks according to its sensitivity level to obtain multiple original file fragments;

[0008] An encryption key is independently generated for each of the original file segments. The corresponding original file segments are encrypted based on the encryption key to obtain each encrypted file segment. Each encrypted file segment is then transmitted to the receiving end.

[0009] After receiving each encrypted file fragment, the receiving end generates an independent decryption key for each encrypted file fragment, decrypts the corresponding encrypted file fragment based on the decryption key, restores the original file fragment, and merges all the decrypted original file fragments to obtain any one file cluster.

[0010] According to a second aspect of the present invention, a large file transfer system is provided, comprising a content recognition layer, a dynamic chunking layer, and an encryption / decryption layer, wherein the content recognition layer and the dynamic chunking layer are located at the sending end, and the encryption / decryption layer is located at the sending end and the receiving end, respectively.

[0011] The content recognition layer is used to identify and classify large input files, and to allocate each identified file to a corresponding file cluster according to its sensitivity level. Each file cluster has a corresponding sensitivity level.

[0012] The dynamic segmentation layer is used to segment any file cluster into multiple original file fragments based on the sensitivity level of the file cluster.

[0013] The encryption / decryption layer is configured to: generate an independent encryption key for each of the original file fragments at the sending end; encrypt the corresponding original file fragments based on the encryption key to obtain each encrypted file fragment; transmit each encrypted file fragment to the receiving end; and after receiving each encrypted file fragment, generate an independent decryption key for each encrypted file fragment at the receiving end; decrypt the corresponding encrypted file fragments based on the decryption key to restore the original file fragments; and merge all the decrypted original file fragments to obtain the arbitrary file cluster.

[0014] This invention provides a method and system for transferring large files, which divides large files into multiple file clusters according to their sensitivity, with each file cluster having a different sensitivity. Subsequently, the file clusters are dynamically segmented based on their sensitivity, and encryption and decryption keys are independently generated for each file segment, thereby enhancing the security and tamper-proof capability of large file transfer. Attached Figure Description

[0015] Figure 1 A flowchart of a large file transfer method provided in one embodiment of the present invention;

[0016] Figure 2 A diagram illustrating the working principle of large file transfer;

[0017] Figure 3 This is a structural block diagram of a large file transfer system provided in one embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined with each other to form feasible technical solutions. Such combinations are not constrained by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0019] The purpose of this invention is to realize a method for encrypting and preventing tampering of large files during transmission, so as to meet the security, integrity and traceability requirements of large file transmission in the national spatial planning implementation monitoring network.

[0020] Figure 1 A flowchart of a large file transfer method according to an embodiment of the present invention is shown, as follows: Figure 1 As shown, the method includes the following steps:

[0021] Step 1: Identify and classify the large input files. Each identified file is assigned to a corresponding file cluster based on its sensitivity level. Each file cluster has a corresponding sensitivity level.

[0022] Understandably, see Figure 2 This step involves identifying and classifying large files, assigning different files to different file clusters.

[0023] Specifically, the content recognition layer is the foundational layer of this invention. It is primarily responsible for identifying and classifying large input files, and allocating the identified files to different file clusters based on their sensitivity levels. Each file cluster has a sensitivity level. Sensitivity levels are defined as follows:

[0024] ;

[0025] All files will be configured with 10 sensitivity levels, with the spatial database / attribute database set to sensitivity level 10, which is the highest sensitivity level.

[0026] The content recognition layer contains multiple types of recognizers, each targeting different file characteristics:

[0027] (1) Content recognizer.

[0028] Function: To identify specific text contained in the file content.

[0029] (2) File format recognizer.

[0030] Function: Identifies file formats based on file extensions or binary characteristics. Binary characteristic identification helps prevent file extension spoofing.

[0031] (3) File name regular expression matching recognizer.

[0032] Function: To match certain files based on regular expressions.

[0033] This invention employs multiple identifiers to identify individual files within a large file system, and assigns the identified files to file clusters corresponding to their sensitivity levels. The embodiments of this invention define file sensitivity levels, decompose large files into file clusters of different sensitivity levels through content recognition, and dynamically segment these file clusters based on data sensitivity, achieving a balance between security and transmission efficiency.

[0034] Step 2: For any file cluster, divide the file cluster into blocks according to the sensitivity level of the file cluster to obtain multiple original file fragments.

[0035] Understandably, encryption and decryption are performed on a file cluster basis. This step intelligently segments the file clusters based on the sensitivity of the data within them and determines the size of each segment. After content recognition, the files have been categorized into file clusters with different sensitivity levels. The dynamic segmentation layer primarily performs secondary segmentation on the file clusters, with the segment size dynamically calculated based on the sensitivity level. High-sensitivity file clusters prioritize ensuring transmission integrity, while low-sensitivity file clusters prioritize ensuring transmission efficiency.

[0036] Specifically, the block size of any file cluster is calculated based on its sensitivity level and data size. ;

[0037] in, The block size of the file cluster. The maximum fragment size, This is the fragment size adjustment factor. Sensitivity level for file clusters, This represents the data size of the file cluster.

[0038] Based on the block size corresponding to any file cluster, divide any file cluster into multiple original file fragments.

[0039] This invention addresses the low overall encryption and decryption efficiency of large files and the complex key management issues inherent in traditional block encryption techniques. It employs a content-recognition-based dynamic block segmentation method, differentiating data based on its sensitivity. Highly sensitive data is segmented into smaller blocks to ensure security, while less sensitive data is segmented into larger blocks to improve transmission efficiency. The HKDF key derivation mechanism avoids the complexity of storing keys separately for each block.

[0040] Step 3: Generate an encryption key for each of the original file segments independently, encrypt the corresponding original file segments based on the encryption key to obtain each encrypted file segment, and transmit each encrypted file segment to the receiving end.

[0041] Understandably, after dividing the file cluster into multiple original file fragments, an independent encryption key is generated for each original file fragment.

[0042] Specifically, based on the master key and the unique identifier of each original file fragment, the encryption key for each of the original file fragments is generated using the HKDF-SHA256 key derivation algorithm: ;

[0043] in, This represents the encryption key for the i-th original file fragment. Master key It is a unique identifier for the i-th original file fragment.

[0044] Each original file fragment is encrypted using the generated encryption key to obtain encrypted file fragments, and then each encrypted file fragment is transmitted to the receiving end.

[0045] Step 4: After receiving each encrypted file fragment at the receiving end, an independent decryption key is generated for each encrypted file fragment. Based on the decryption key, the corresponding encrypted file fragment is decrypted to restore the original file fragment. All the decrypted original file fragments are merged to obtain the arbitrary file cluster.

[0046] Understandably, after receiving each encrypted file fragment, the receiving end generates a decryption key independently for each encrypted file fragment. The algorithm for generating the decryption key is the same as the algorithm for generating the encryption key. Assuming that the master keys of the encryption and decryption ends are consistent, the encryption and decryption key of each file fragment can be completely determined by the fragment's unique identifier.

[0047] Specifically, based on the master key and the unique identifier of each original file fragment, the encryption key for each original file fragment is generated using the HKDF-SHA256 key derivation algorithm: ;

[0048] in, This represents the decryption key for the i-th encrypted file fragment. Master key It is a unique identifier for the i-th encrypted file fragment.

[0049] The corresponding encrypted file fragments are decrypted using independently generated decryption keys to obtain the original file fragments before encryption. Then, each decrypted original file fragment is merged to obtain the original file cluster.

[0050] Steps 2 to 4 are performed on each file cluster in the large file. That is, when the receiving end receives each encrypted and decrypted file cluster, the file clusters are merged to obtain the large file that has been transmitted.

[0051] It should be noted that during the transfer of large files, integrity verification of the transferred large files is required. Specifically, in this embodiment of the invention, a signature chain is constructed for the spatial database and / or attribute database of the large file.

[0052] Specifically, the spatial database and / or attribute database includes multiple data tables, each containing multiple spatial features. Feature-level, feature-class-level, and database-level feature codes are calculated for both the spatial and / or attribute databases. Based on these feature codes, feature-class-level, and database-level feature codes, a feature code chain is constructed according to their hierarchical relationship, and timestamps and sequence numbers are added. Calculating the feature code chain is computationally intensive; timestamps are added to prevent replay attacks, and sequence numbers are added to identify the feature code chain.

[0053] (1) Element-level feature code calculation:

[0054] Calculate the SHA-256 hash value for each spatial element (row) to generate an element-level feature code. Use a batch processing mechanism to perform parallel hash calculations for every 1000 elements as a group.

[0055] Element-level feature codes are represented as follows:

[0056] ;

[0057] in, SHA-256 represents the hash value of each spatial element, and is a hash value calculation method. This indicates that for the j-th spatial element Perform serialization.

[0058] (2) Generate feature class (table) level feature codes based on feature level feature codes.

[0059] Feature class level feature codes are represented as follows:

[0060] ;

[0061] in, Represents the feature code at the element class level. For hash tree generation methods, , ... This represents the feature-level feature code of m spatial features in the data table. A hash value representing the data structure of a data table, including the table structure and protocol format.

[0062] (3) Generate database-level feature codes based on feature class-level feature codes.

[0063] Calculate the database-level feature code of the spatial data and / or the attribute database based on the feature class-level feature code of each data table:

[0064] ;

[0065] in, Represents database-level feature codes. This represents the feature class-level feature code of n data tables. It refers to the hash value of metadata in the database.

[0066] (4) Feature code chain construction:

[0067] Construct a feature code chain by hierarchically assigning feature codes at the element level, element class level, and database level, and add timestamps and sequence numbers to prevent replay attacks.

[0068] The signature chain is represented as follows:

[0069] ;

[0070] in, Represents the feature code chain, For the first A database-level feature code, For timestamps, This is the serial number.

[0071] This invention performs feature code calculations on structured spatial databases or attribute databases in large files at three levels: feature, feature class, and database. It constructs a feature code chain from the feature level to the database level and establishes a multi-level integrity verification system.

[0072] The sending end sends the signature code chain to the receiving end; after the receiving end decrypts the original file cluster, it calculates the signature code chain based on the spatial database and / or attribute database within it, and compares the signature code chain generated by the receiving end with the signature code chain sent by the sending end to verify the transmission integrity of large files.

[0073] When data is tampered with, the specific data element or element class can be precisely located through the breakpoint of the feature code chain, ensuring the integrity of spatial or attribute data during transmission and achieving precise location and traceable verification of tampering. Compared to traditional technologies that can only detect "whether it has been tampered with," this invention can answer "where it was tampered with" and "what was tampered with." Therefore, this invention has significant advantages in tamper detection accuracy and location capability.

[0074] See Figure 3 This invention illustrates a large file transfer system according to an embodiment of the present invention. The system includes a content recognition layer 301, a dynamic chunking layer 302, and an encryption / decryption layer 303. The content recognition layer 301 and the dynamic chunking layer 302 are located at the sending end 10, and the encryption / decryption layer 303 is located at the sending end 10 and the receiving end 20, respectively.

[0075] The content recognition layer 301 is used to recognize and classify large input files, and to allocate each recognized file to a corresponding file cluster according to the sensitivity level configuration, with each file cluster having a corresponding sensitivity level.

[0076] The dynamic block layer 302 is used to divide any file cluster into blocks according to the sensitivity level of the file cluster, thereby obtaining multiple original file fragments.

[0077] The encryption / decryption layer 303 is used to generate an independent encryption key for each of the original file fragments at the sending end 10, encrypt the corresponding original file fragments based on the encryption key to obtain each encrypted file fragment, and transmit each encrypted file fragment to the receiving end 20; and after receiving each encrypted file fragment, the receiving end 20 generates an independent decryption key for each encrypted file fragment, decrypts the corresponding encrypted file fragment based on the decryption key to restore the original file fragment, and merges all the decrypted original file fragments to obtain the arbitrary file cluster.

[0078] The large file transfer system also includes a layered feature code layer 304, which constructs a feature code chain for the spatial database and / or attribute database in the large file, specifically including:

[0079] Calculate feature-level feature codes, feature class-level feature codes, and database-level feature codes for the spatial database and / or the attribute database, respectively;

[0080] Based on the element-level feature code, the element class-level feature code, and the database-level feature code, a feature code chain is constructed according to the hierarchical relationship, and a timestamp and sequence number are added.

[0081] After receiving a large file, the receiving end 20 calculates a feature code chain based on the spatial database and / or attribute database contained therein, and compares the feature code chain generated by the receiving end with the feature code chain sent by the sending end to verify the transmission integrity of the large file.

[0082] It is understood that the large file transfer system provided by the present invention corresponds to the large file transfer method provided in the foregoing embodiments. The relevant technical features of the large file transfer system can be referred to the relevant technical features of the large file transfer method, and will not be repeated here.

[0083] The large file transfer method and system provided in this invention have the following beneficial effects:

[0084] (1) By constructing a dynamic segmentation method based on content recognition, this invention can identify sensitive spatial databases and attribute databases contained in large files, and achieve encryption granularity that matches the logical structure of spatial data.

[0085] (2) Existing integrity verification technologies mainly focus on the overall integrity of the document, making it difficult to accurately locate tampering at the specific data element or element class level. This results in insufficient tampering detection accuracy because they cannot provide effective evidence and location information. This invention generates a hierarchical fingerprint chain with strong correlation by extracting features from multiple levels, from elements (rows) / element classes (tables) to the database level, thereby achieving accurate location and traceable verification of tampering.

[0086] (3) In large file encryption scenarios, key management is complex, access control granularity is insufficient, and it is difficult to achieve fine-grained permission management and key isolation, resulting in low key management efficiency. This invention achieves key isolation and fine-grained access control by generating encryption keys independently for each data block, thereby optimizing key management efficiency.

[0087] (4) Existing solutions fail to establish a hierarchical feature code chain from the element level to the database level, thus failing to form a complete data gene map and resulting in an imperfect data integrity proof system. This invention constructs a hierarchical feature code chain, associates and signs feature codes at each level, and forms a complete data integrity proof system, deeply integrating data structure, content features and integrity constraints.

[0088] (5) There is a lack of encryption and integrity protection schemes specifically for large files containing spatial databases, which fails to fully utilize the structured features and semantic information of spatial data, resulting in insufficient utilization of spatial database characteristics. This invention establishes a specialized protection mechanism for spatial elements and attribute data by fully utilizing the hierarchical structural features of spatial data, effectively identifying and processing sensitive information in spatial databases.

[0089] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0090] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0091] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0092] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0093] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0094] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0095] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A large file transfer method, characterized by, include: The system identifies and classifies large input files, and assigns each identified file to a corresponding file cluster based on its sensitivity level. Each file cluster has a corresponding sensitivity level. For any file cluster, the file cluster is divided into blocks according to its sensitivity level to obtain multiple original file fragments; An encryption key is independently generated for each of the original file segments. The corresponding original file segments are encrypted based on the encryption key to obtain each encrypted file segment. Each encrypted file segment is then transmitted to the receiving end. After receiving each encrypted file fragment, the receiving end generates an independent decryption key for each encrypted file fragment, decrypts the corresponding encrypted file fragment based on the decryption key, restores the original file fragment, and merges all the decrypted original file fragments to obtain any one file cluster.

2. The large file transfer method of claim 1, wherein, The process of identifying and classifying large input files includes: The large input files are identified and classified based on the content recognition layer, which includes a content recognizer, a file format recognizer, and a filename regular expression matching recognizer. The content recognizer is used to identify text that includes the content of a specific file. The file format recognizer is used to identify file formats based on file extensions or binary characteristics; The filename regular expression matching recognizer is used to match files based on regular expressions.

3. The large file transfer method of claim 1, wherein, For any given file cluster, based on its sensitivity level, the file cluster is divided into blocks to obtain multiple original file fragments, including: Calculate the block size of any given file cluster based on its sensitivity level and data size: ， in, The block size of the file cluster. The maximum fragment size, This is the fragment size adjustment factor. Sensitivity level for file clusters, The data size of the file cluster; Based on the block size corresponding to any file cluster, the file cluster is divided into multiple original file fragments.

4. The large file transfer method according to claim 1, characterized in that, The step of generating an independent encryption key for each of the original file fragments includes: Based on the master key and the unique identifier of each original file fragment, the encryption key for each original file fragment is generated using the HKDF-SHA256 key derivation algorithm: ， in, This represents the encryption key for the i-th original file fragment. Master key It is a unique identifier for the i-th original file fragment.

5. The method for transferring large files according to claim 1, characterized in that, After receiving each encrypted file fragment at the receiving end, generating an independent decryption key for each encrypted file fragment includes: Based on the master key and the unique identifier of each original file fragment, the encryption key for each original file fragment is generated using the HKDF-SHA256 key derivation algorithm: ， in, This represents the decryption key for the i-th encrypted file fragment. Master key It is a unique identifier for the i-th encrypted file fragment.

6. The method for transferring large files according to claim 1, characterized in that, The spatial database and attribute database in the large file have the highest sensitivity level.

7. The method for transferring large files according to claim 6, characterized in that, Also includes: Constructing a feature code chain for the spatial database and / or the attribute database includes: Calculate feature-level feature codes, feature class-level feature codes, and database-level feature codes for the spatial database and / or the attribute database, respectively; Based on the element-level feature code, the element class-level feature code, and the database-level feature code, a feature code chain is constructed according to the hierarchical relationship, and a timestamp and sequence number are added to the feature code chain.

8. The method for transferring large files according to claim 7, characterized in that, The calculation of feature-level feature codes, feature class-level feature codes, and database-level feature codes for the spatial database and / or the attribute database respectively includes: The SHA-256 hash value is calculated for each spatial feature in each table of the spatial database and / or the attribute database in batches and in parallel, generating an feature-level feature code for each spatial feature: ， in, SHA-256 represents the hash value of each spatial element, and is a hash value calculation method. This indicates that for the j-th spatial element Perform serialization; For each data table, calculate the feature class-level feature code for each data table based on the feature-level feature code of each spatial feature: ， in, Represents the feature code at the element class level. For hash tree generation methods, , ... This represents the feature-level feature code of m spatial features in the data table. A hash value representing the data structure of a data table, including the table structure and spatial reference; Calculate the database-level feature codes for the spatial database and / or the attribute database based on the feature class-level feature codes for each data table: ， in, Represents database-level feature codes. This represents the feature class-level feature code of n data tables. It refers to the hash value of metadata in the database; The feature code chain is represented as follows: ， in, Represents the signature chain, For the first A database-level feature code, For timestamps, This is the serial number.

9. The method for transferring large files according to claim 7 or 8, characterized in that, Also includes: Send the feature code chain to the receiving end; After the original file cluster is obtained through decryption at the receiving end, a feature code chain is calculated at the receiving end based on the spatial database and / or attribute database therein. The feature code chain generated at the receiving end is compared with the feature code chain sent by the sending end to verify the transmission integrity of large files.

10. A large file transfer system, characterized in that, The system includes a content recognition layer, a dynamic segmentation layer, and an encryption / decryption layer. The content recognition layer and the dynamic segmentation layer are located at the sending end, and the encryption / decryption layer is located at the sending end and the receiving end, respectively. The content recognition layer is used to identify and classify large input files, and to allocate each identified file to a corresponding file cluster according to its sensitivity level. Each file cluster has a corresponding sensitivity level. The dynamic segmentation layer is used to segment any file cluster into multiple original file fragments based on the sensitivity level of the file cluster. The encryption / decryption layer is used to generate an encryption key independently for each of the original file segments at the sending end, encrypt the corresponding original file segments based on the encryption key to obtain each encrypted file segment, and transmit each encrypted file segment to the receiving end. After receiving each encrypted file fragment at the receiving end, an independent decryption key is generated for each encrypted file fragment at the receiving end. Based on the decryption key, the corresponding encrypted file fragment is decrypted to restore the original file fragment. All the decrypted original file fragments are merged to obtain the arbitrary file cluster.

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