An Image Semantic Communication Method and Application Based on Encryption Algorithm

Abstract

The present invention discloses an image semantic communication method and application based on an encryption algorithm. The method includes: dividing an input image into several semantic information units; calculating the risk level scores of each semantic information unit through a security risk discrimination algorithm based on the task relevance scores provided by a task knowledge base and the storage space of the semantic information units, and classifying the high-security-risk information units and the low-security-risk information units; encrypting the high-security-risk information units using a quantum encryption algorithm and encrypting the low-security-risk information units using a classical encryption algorithm; transmitting the encrypted semantic information units to a receiving end through a communication channel, and decrypting the semantic information units separately at the receiving end and reconstructing them into a complete image. It can solve the problems that the existing image semantic communication using quantum encryption technology has limited communication bandwidth and transmission capacity and the low security of classical encryption algorithms.

Description

Technical Field

[0001] The present application relates to the field of encrypted communication technologies, and particularly to an image semantic communication method, apparatus, electronic device, and computer-readable storage medium based on an encryption algorithm. Background Art

[0002] As an emerging communication technology, semantic communication can greatly alleviate the problem of the current shortage of communication bandwidth and the rapid increase in data volume, and is one of the important development directions in the communication field. Especially for image information transmission, semantic communication technology can significantly reduce the amount of data to be transmitted while ensuring the visual quality of the image, improving communication efficiency. However, in fields with high security and confidentiality requirements, how to enhance the encryption of image semantic communication technology and improve security is one of the key issues in promoting the development of semantic communication technology.

[0003] Quantum encryption technologies represented by quantum key distribution and quantum direct secure communication are relatively secure technical means in the current information security field. However, quantum encryption technologies usually face problems such as limited communication bandwidth and limited transmission capacity; classical encryption algorithms represented by the RSA algorithm have a high throughput, but current classical encryption algorithms have the security risk of being broken by quantum computing. Image semantic communication technology has the ability to analyze semantic information in images, providing an effective way to analyze the security risks of different information in images. But how to analyze the security risks of different information in images, effectively combine quantum encryption algorithms and classical encryption algorithms, and simultaneously achieve the efficiency and security of image semantic communication is still an urgent problem to be solved. Summary of the Invention

[0004] In order to overcome the defects of the above-mentioned prior art, embodiments of the present invention provide an image semantic communication method and application based on an encryption algorithm, which can solve the problems of limited communication bandwidth and transmission capacity existing in the use of quantum encryption technology in existing image semantic communication, and the problem of low security in the use of classical encryption algorithms.

[0005] On the one hand, an embodiment of the present invention proposes an image semantic communication method based on an encryption algorithm, including: segmenting an input image into several semantic information units through a semantic segmentation unit, where the semantic information units include high-security-risk information units related to task objectives and low-security-risk information units related to the background; calculating the risk level scores of each semantic information unit through a security risk discrimination algorithm based on the task relevance scores provided by the task knowledge base and the storage space of the semantic information units, and classifying the high-security-risk information units and the low-security-risk information units according to the risk level scores; encrypting the high-security-risk information units using a quantum encryption algorithm and encrypting the low-security-risk information units using a classical encryption algorithm; transmitting the encrypted semantic information units to a receiving end through a communication channel, and decrypting the semantic information units at the receiving end and reconstructing them into a complete image respectively.

[0006] In an embodiment of the present invention, the semantic segmentation unit includes a Yolo-World model and a SAM model. The Yolo-World model extracts regions based on the task objectives in the task knowledge base, and the SAM model performs fine segmentation on the extracted regions to generate independent semantic information units.

[0007] In an embodiment of the present invention, the security risk discrimination algorithm calculates the risk level score through the following formula: ; where is the task relevance score of the semantic information unit, is the storage space size.

[0008] In an embodiment of the present invention, the quantum encryption algorithm includes quantum key distribution or quantum direct secure communication. During the encryption process, it is monitored in real time whether the channel is eavesdropped, and the high-security-risk information units are encrypted in a one-time pad manner.

[0009] In an embodiment of the present invention, the communication channel transmission adopts an adaptive bandwidth allocation algorithm, including: dynamically allocating communication bandwidth according to the task relevance score and storage space of the semantic information units, and converting the semantic information units with a task relevance lower than a preset value into tag transmission.

[0010] In an embodiment of the present invention, the image reconstruction is based on the OpenCV framework, and the decrypted semantic information units are fused with the three-dimensional data provided by the domain knowledge base to generate a reconstructed image with optimized visual quality.

[0011] In an embodiment of the present invention, the task knowledge base contains task objective entities and task relevance scores, and the domain knowledge base contains three-dimensional data of task objective entities and label-associated image data.

[0012] On the other hand, an embodiment of the present invention further provides an image semantic communication device based on an encryption algorithm, including: an image semantic segmentation module, configured to segment an input image into a plurality of semantic information units through a semantic segmentation unit, where the semantic information units include high-security-risk information units related to task objectives and low-security-risk information units related to the background; an information unit classification module, configured to calculate the risk level scores of each of the semantic information units through a security risk discrimination algorithm based on the task relevance scores provided by the task knowledge base and the storage space of the semantic information units, and classify the high-security-risk information units and the low-security-risk information units according to the risk level scores; an information unit encryption module, configured to encrypt the high-security-risk information units using a quantum encryption algorithm and encrypt the low-security-risk information units using a classical encryption algorithm; an image reconstruction module, configured to transmit the encrypted semantic information units to a receiving end through a communication channel, and reconstruct the semantic information units into a complete image after decrypting them respectively at the receiving end.

[0013] On the other hand, an embodiment of the present invention further provides an electronic device, including: a memory and one or more processors connected to the memory, where the memory stores a computer program, and the processor is configured to execute the computer program to implement the image semantic communication method based on an encryption algorithm as described in any one of the above embodiments.

[0014] On the other hand, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are configured to execute the image semantic communication method based on an encryption algorithm as described in any one of the above embodiments.

[0015] As can be seen from the above, compared with the prior art, the above embodiments of the present invention can at least have one or more of the following beneficial effects:

[0016] The present invention proposes a secure image semantic communication method combining quantum-classical encryption algorithms. Specifically, by analyzing the semantic information contained in the image and decoupling it into different semantic information units, analyzing the security risks of different information units, encrypting the high-security-risk information units using a quantum encryption algorithm, and encrypting the low-security-risk information units using a classical encryption algorithm, the advantages of the quantum encryption algorithm and the classical encryption algorithm are effectively combined, avoiding the risk of information leakage caused by quantum computing faced by traditional encryption algorithms, and realizing high-efficiency and high-security image semantic communication; the proposed security risk assessment method comprehensively considers the task relevance and storage space size of the information units, ensuring that the information units with small storage space and high relevance are preferentially encrypted by quantum encryption technology, well overcoming the limitation of low throughput of quantum encryption technology, and protecting the core information in the image through limited quantum keys. Brief Description of the Drawings

[0017] The drawings described herein are provided to further understand the present invention and form a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0018] Figure 1 It is a flowchart of an image semantic communication method based on an encryption algorithm provided by an embodiment of the present invention;

[0019] Figure 2 It is a schematic diagram of the execution logic of an image semantic communication method based on an encryption algorithm provided by an embodiment of the present invention;

[0020] Figure 3 It is a specific implementation flowchart of an image semantic communication method based on an encryption algorithm provided by an embodiment of the present invention;

[0021] Figure 4 It is a schematic diagram of the structure of an image semantic communication device based on an encryption algorithm provided by an embodiment of the present invention;

[0022] Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention;

[0023] Figure 6 It is a schematic diagram of the structure of a computer-readable storage medium provided by an embodiment of the present invention. Detailed Description of the Embodiments

[0024] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described below with reference to the drawings and in conjunction with the embodiments.

[0025] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments, and all should fall within the protection scope of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] It should also be noted that the division of multiple embodiments in the present invention is only for convenience of description and should not constitute a special limitation. The features in various embodiments can be combined and cross-referenced without conflict.

[0028] As Figure 1 shown, the first embodiment of the present invention proposes an image semantic communication method based on an encryption algorithm, for example, including: Step S1, dividing an input image into several semantic information units through a semantic segmentation unit, where the semantic information units include high-security-risk information units related to task objectives and low-security-risk information units related to the background; Step S2, based on the task relevance scores provided by the task knowledge base and the storage space of the semantic information units, calculating the risk level scores of each semantic information unit through a security risk discrimination algorithm, and classifying the high-security-risk information units and low-security-risk information units according to the risk level scores; Step S3, encrypting the high-security-risk information units using a quantum encryption algorithm and encrypting the low-security-risk information units using a classical encryption algorithm; Step S4, transmitting the encrypted semantic information units to a receiving end through a communication channel, and decrypting the semantic information units at the receiving end respectively and reconstructing them into a complete image.

[0029] Specifically, as Figure 2 shown, the method is implemented by these functional units: semantic segmentation, information organization, encoding, decoding, information supplementation, image reconstruction, task knowledge base, domain knowledge base, classical encryption algorithm, and quantum encryption algorithm. Among them, the task knowledge base mainly includes typical tasks in the application scenario, task objective entities that often appear in the image, and task relevance scores. Its function is to provide guidance for semantic segmentation and information organization. The domain knowledge base mainly includes task objective entities and three-dimensional data that often appear in the image in the application scenario. Its function is to provide complete image data based on labels for image reconstruction and improve the visual quality of the image.

[0030] The semantic segmentation unit is composed of, for example, the Yolo-World model and the Segment Anything Model (SAM) model. First, under the support of the task knowledge base, the task objectives (such as cars, pedestrians, houses, etc.) are embedded in the Yolo-World in text form, the regions in the image that contain the task objectives are extracted, the region coordinates are obtained and input into the SAM. Then, the SAM segments the targets in the region into independent information units, obtaining several semantic information units and their coordinates.

[0031] The information organization unit includes an adaptive bandwidth allocation algorithm and a security risk discrimination algorithm. First, the adaptive bandwidth allocation algorithm allocates bandwidth according to the task relevance of different information units, compresses the image data according to the allocated bandwidth, and at the same time converts the information units with extremely low task relevance into tags to improve the utilization rate of the communication bandwidth. Then, according to the task relevance, different information units are divided into two categories: high security risk and low security risk, and are input into different channels for transmission.

[0032] The coding module is the source encoding / decoding and channel encoding / decoding module in the communication system. This module is responsible for encoding the semantic information units so that they become information sequences suitable for being sent to the communication channel, and decoding the information sequences at the receiving end to restore them to semantic information units.

[0033] Classic encryption algorithms encrypt and decrypt the relatively low security risk information sequences after encoding through classic encryption algorithms represented by algorithms such as RSA and AED. Quantum encryption algorithms encrypt and decrypt the relatively high security risk information sequences after encoding through quantum cryptography technologies represented by quantum key distribution, and when conditions permit, quantum direct secure communication technologies can also be directly used for secure transmission.

[0034] The information supplement module is based on the domain knowledge base and provides corresponding three-dimensional image data for the image reconstruction unit according to the received tag data.

[0035] The image reconstruction unit generates a reconstructed image based on the image fusion algorithm designed based on the OpenCV framework, according to the received image data and positioning data.

[0036] Therefore, the method takes image semantic communication technology as the core, is based on quantum encryption algorithms and classic encryption algorithms, organizes the information units in the image through semantic analysis, selects different encryption methods for encryption according to the security risk, encrypts the information units with high security risk through quantum encryption algorithms, and encrypts the information units with low security risk through classic encryption algorithms. It not only realizes the transmission of high security risk information units through quantum encryption algorithms, but also overcomes the problem of low transmission efficiency of quantum encryption algorithms, effectively combines the advantages of quantum encryption algorithms and classic encryption algorithms, and realizes high-efficiency and high-security image semantic communication.

[0037] The following will combine Figure 3 the steps shown below to elaborate in detail on the solution and effects of this application:

[0038] Step (1): Initialize the task knowledge base and the domain knowledge base, set the task requirements and feed them forward to the semantic segmentation unit.

[0039] Step (2): Input the image into the semantic segmentation unit, perform semantic segmentation on the image according to the provided task objectives, decouple the image into several semantic information units, and use the segmented background as the background information unit.

[0040] Step (3): Input all information units (including the background information unit) into the information organization unit, and perform bandwidth allocation with the product of the task relevance score provided by the task knowledge base and the storage space of the information unit as the weight. At the same time, divide the information units into two categories: high-risk and low-risk according to the task relevance score. Considering the limited throughput of the quantum encryption algorithm, information units with high relevance and small storage space should be transmitted preferentially. Therefore, this embodiment proposes the following security risk calculation method shown by the formula to calculate the security risk scores of all semantic information units. For example, input the 50% semantic information units with the highest security risk scores into the quantum encryption algorithm module, and the latter 50% into the classical encryption algorithm module. It should be noted that the background information unit does not contain task-related information and has no task relevance score, and is directly classified into the classical encryption algorithm.

[0041] ;

[0042] In the formula, , and respectively represent the relevance score of the semantic information unit (from the task knowledge base), the risk level score, and the storage space size.

[0043] Step (4): Encode all semantic information units to generate an information sequence.

[0044] Step (5): The classical encryption algorithm module uses the RSA algorithm to output the public key to the sender and encrypt the information sequence of the low security risk semantic information units (including the background information unit).

[0045] Step (6): The quantum encryption algorithm distributes the key to the sender and the output end in advance through the quantum key distribution system, encrypts the information sequence of the high security risk semantic information units in a one-time pad manner, and monitors in real time whether the channel is wiretapped during the process of quantum key distribution; or directly transmits the information sequence of the high security risk semantic information units through the quantum direct secure communication system.

[0046] Step (7): Modulate the encrypted information sequence into a signal form suitable for transmission (such as a radio frequency signal), and transmit it through a communication system. If a quantum direct secure communication system is adopted, only the information sequence encrypted by the classical encryption algorithm needs to be transmitted.

[0047] Step (8): Decrypt the low-security-risk information sequence with the private key of the RSA algorithm, and decrypt the high-security-risk information sequence with the key of quantum key distribution. If a quantum direct secure communication scheme is adopted, the decoding is directly completed through the quantum direct secure communication system.

[0048] Step (9): Output the decrypted information sequence to the decoding module, and restore the information sequence to semantic information units.

[0049] Step (10): Obtain the tag data in the information sequence, and extract the corresponding image data from the domain knowledge base.

[0050] Step 11: Fuse the extracted image data and the received semantic information units into the background information unit through an image fusion algorithm to generate a reconstructed image.

[0051] In summary, the first embodiment of the present invention proposes an image semantic communication method based on an encryption algorithm. By analyzing the semantic information contained in the image and decoupling it into different semantic information units, analyzing the security risks of different information units, encrypting the information units with high security risks using a quantum encryption algorithm, and encrypting the information units with low security risks using a classical encryption algorithm, the advantages of the quantum encryption algorithm and the classical encryption algorithm are effectively combined. While avoiding the risk of information leakage caused by quantum computing faced by traditional encryption algorithms, high-efficiency and high-security image semantic communication is achieved; the proposed security risk assessment method comprehensively considers the task relevance and storage space size of the information units, ensures that the information units with small storage space and high relevance are preferentially encrypted by quantum encryption technology, and well overcomes the limitation of low throughput of quantum encryption technology, protecting the core information in the image with limited quantum keys.

[0052] In addition, as Figure 4 shown, the second embodiment of the present invention also proposes an image semantic communication device 20 based on an encryption algorithm, for example, including: an image semantic segmentation module 201, an information unit classification module 202, an information unit encryption module 203, and an image reconstruction module 204.

[0053] Among them, the image semantic segmentation module 201 is used to segment the input image into several semantic information units through the semantic segmentation unit. The semantic information units include high-security-risk information units related to the task target and low-security-risk information units related to the background. The information unit classification module 202 is used to calculate the risk level scores of each of the semantic information units through a security risk discrimination algorithm based on the task relevance scores provided by the task knowledge base and the storage space of the semantic information units, and classify the high-security-risk information units and the low-security-risk information units according to the risk level scores. The information unit encryption module 203 is used to encrypt the high-security-risk information units by using a quantum encryption algorithm and encrypt the low-security-risk information units by using a classical encryption algorithm. The image reconstruction module 204 is used to transmit the encrypted semantic information units to the receiving end through a communication channel, and reconstruct the semantic information units into a complete image after decrypting them respectively at the receiving end.

[0054] The image semantic communication method based on the encryption algorithm implemented by the image semantic communication device 20 disclosed in the second embodiment of the present invention is as described in the foregoing first embodiment, so details will not be described herein again. Optionally, each module in the second embodiment and the above other operations or functions are respectively for implementing the method described in the first embodiment, and the beneficial effects of the image semantic communication device 20 based on the encryption algorithm provided in this embodiment are the same as those of the image semantic communication method based on the encryption algorithm provided in the foregoing first embodiment. For the sake of brevity, they will not be elaborated herein.

[0055] As Figure 5 shown, the third embodiment of the present invention further proposes an electronic device 30, for example, including: at least one processor 31 and at least one memory 32. Among them, the memory 32 stores a computer program. When the computer program is executed by the processor 31, the processor 31 is caused to execute the method described in the first embodiment, and the beneficial effects of the electronic device 30 provided in this embodiment are the same as those of the image semantic communication method based on the encryption algorithm provided in the first embodiment.

[0056] As Figure 6 shown, the fourth embodiment of the present invention further provides a computer-readable storage medium 40, on which a computer program is stored. When the program is executed by a processor, the steps of the above method are implemented, and the beneficial effects of the computer-readable storage medium 40 provided in this embodiment are the same as those of the image semantic communication method based on the encryption algorithm provided in the first embodiment.

[0057] Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0058] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be adopted in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0059] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0060] In the several embodiments provided by this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0061] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0062] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0063] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes: various media such as USB flash drives, read-only memories (ROM), random access memories (RAM), external hard drives, magnetic disks, or optical discs that can store program codes.

[0064] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: flash drives, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs, etc.

[0065] The above are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. After considering the specification and practicing the present disclosure herein, those skilled in the art will readily think of other implementations of the present disclosure. This application aims to cover any variations, uses, or adaptive changes of the present disclosure, which follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

[0066] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as within the scope described in this specification.

[0067] Those skilled in the art can easily understand that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An image semantic communication method based on an encryption algorithm, characterized in that, Comprising: The input image is segmented into a number of semantic information units by a semantic segmentation unit, and the segmented background is used as a background information unit; Based on the task relevance scores provided by the task knowledge base and the storage space of the semantic information units, the risk level scores of each semantic information unit are calculated by a security risk discrimination algorithm, and high-security-risk information units and low-security-risk information units are classified according to the risk level scores; The quantum encryption algorithm is used to encrypt the high-security-risk information units, and the classical encryption algorithm is used to encrypt the low-security-risk information units; The encrypted semantic information units are transmitted to the receiving end through a communication channel, and the semantic information units are respectively decrypted at the receiving end and reconstructed into a complete image.

2. The method for image semantic communication based on encryption algorithm according to claim 1, wherein The semantic segmentation unit includes a Yolo-World model and a SAM model. The Yolo-World model performs region extraction based on the task objectives in the task knowledge base, and the SAM model performs fine segmentation on the extracted regions to generate independent semantic information units.

3. The method for image semantic communication based on encryption algorithm according to claim 1, characterized in that The security risk discrimination algorithm calculates the risk level scores through the following formula: ； Among them, is the task relevance score of the semantic information unit, is the storage space size.

4. The image semantic communication method based on an encryption algorithm according to claim 1, wherein The quantum encryption algorithm includes quantum key distribution or quantum direct secure communication. During the encryption process, it is monitored in real time whether the channel is wiretapped, and the high-security-risk information units are encrypted in a one-time pad manner.

5. The method for image semantic communication based on an encryption algorithm according to claim 1, characterized in that, The communication channel transmission adopts an adaptive bandwidth allocation algorithm, including: dynamically allocating communication bandwidth according to the task relevance scores and storage space of the semantic information units, and converting the semantic information units with a task relevance lower than a preset value into tag transmissions.

6. The image semantic communication method based on an encryption algorithm according to claim 1, wherein The image reconstruction is based on the OpenCV framework, and the decrypted semantic information units are fused with the three-dimensional data provided by the domain knowledge base to generate a reconstructed image with optimized visual quality.

7. The method for image semantic communication based on an encryption algorithm according to claim 6, wherein The task knowledge base contains task objective entities and task relevance scores, and the domain knowledge base contains three-dimensional data of task objective entities and label-associated image data.

8. An image semantic communication device based on an encryption algorithm, characterized in that, Comprising: An image semantic segmentation module, configured to segment an input image into a number of semantic information units by a semantic segmentation unit, and use the segmented background as a background information unit; An information unit classification module, configured to calculate the risk level scores of each semantic information unit by a security risk discrimination algorithm based on the task relevance scores provided by the task knowledge base and the storage space of the semantic information units, and classify high-security-risk information units and low-security-risk information units according to the risk level scores; An information unit encryption module, configured to encrypt the high-security-risk information units by using a quantum encryption algorithm and encrypt the low-security-risk information units by using a classical encryption algorithm; An image reconstruction module, configured to transmit the encrypted semantic information units to the receiving end through a communication channel, and respectively decrypt the semantic information units at the receiving end and reconstruct them into a complete image.

9. An electronic device, characterized in that, Comprising: A memory and one or more processors connected to the memory, the memory storing a computer program, and the processors being configured to execute the computer program to implement the image semantic communication method based on an encryption algorithm as recited in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for executing the image semantic communication method based on an encryption algorithm as recited in any one of claims 1-7.

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