Airport information security identification method and device, electronic equipment and storage medium

Abstract

The invention discloses a security identification method and device for airport information, electronic equipment and a storage medium. The method comprises the following steps: acquiring air ticket booking information of a first user, the air ticket booking information at least comprising first biological identification information of the first user; performing feature extraction on first biological recognition information in the air ticket booking information to obtain a first biological recognition feature vector; issuing the first biological recognition feature vector to a target airport corresponding to the air ticket booking information; in response to arrival of the second user at the target airport, acquiring second biological recognition information of the second user; the second biological recognition information is compared with the first biological recognition feature vector, an information recognition result is obtained, and the information recognition result is used for representing whether the second user is the first user or not. According to the invention, the technical problem of low efficiency and safety of processing and identifying airport information in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of information security identification, and in particular to a method, device, electronic equipment and storage medium for secure identification of airport information. Background Art

[0002] In the application field of information identification at airports, data information security becomes a key point because airports manage a large amount of sensitive information. Traditional information identification systems may be at risk of being maliciously tampered with and rely on centralized databases or servers. It is difficult to establish a reliable data sharing and collaboration mechanism among all parties at the airport.

[0003] At present, when airports authenticate users, they usually base their authentication on the information entered by the user when applying for an ID card. The user's identity information is usually not updated in a timely manner, resulting in verification failures or repeated verification when the user is verified on site at the airport, which prolongs the verification time for the user and the airport, and the user's travel experience is low. The existing airport sensitive information identification method mainly deploys corresponding information functions on local servers, and various information security risks are prone to emergencies, especially those involving sensitive information being tampered with and unable to be traced. Relying on the existing information storage and use mode of the airport system, it is difficult to effectively achieve ideal security, resulting in low efficiency and security in the processing and identification of airport information in related technologies.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, electronic device and storage medium for securely identifying airport information, so as to at least solve the technical problem of low efficiency and low security in processing and identifying airport information in the related art.

[0006] According to one aspect of an embodiment of the present application, a method for securely identifying airport information is provided, including: obtaining air ticket booking information of a first user, wherein the air ticket booking information includes at least first biometric information of the first user; performing feature extraction on the first biometric information in the air ticket booking information to obtain a first biometric feature vector; sending the first biometric feature vector to a target airport corresponding to the air ticket booking information; in response to a second user arriving at the target airport, obtaining second biometric information of the second user; comparing the second biometric information with the first biometric feature vector to obtain an information identification result, wherein the information identification result is used to indicate whether the second user is the first user.

[0007] Optionally, sending the first biometric feature vector to the target airport corresponding to the air ticket booking information includes: parsing the air ticket booking information to obtain user travel information; determining the target airport based on the user travel information, and sending the first biometric feature vector to the target airport.

[0008] Optionally, sending the first biometric feature vector to the target airport includes: obtaining a preset random initialization vector and an encryption key of a preset encryption algorithm; using a preset encryption algorithm to encrypt the preset random initialization vector, the encryption key and the first biometric feature vector to obtain an encrypted vector; concatenating the preset random initialization vector and the encryption vector to obtain an encrypted data block, and sending the encrypted data block to the target airport; decrypting the encrypted data block based on the target airport to obtain the first biometric feature vector.

[0009] Optionally, the encrypted data block is decrypted based on the target airport to obtain a first biometric feature vector, including: decrypting the encryption vector in the encrypted data block based on the target airport to obtain a decrypted biometric feature vector and a decrypted random initialization vector; comparing the decrypted random initialization vector with a preset random initialization vector in the encrypted data block to obtain a comparison result, wherein the comparison result is used to characterize whether the decrypted random initialization vector and the preset random initialization vector are consistent; and determining the first biometric feature vector based on the comparison result and the decrypted biometric feature vector.

[0010] Optionally, the second biometric information is compared with the first biometric feature vector to obtain an information recognition result, including: extracting features from the second biometric information to obtain a second biometric feature vector; determining the cosine similarity between the second biometric feature vector and the first biometric feature vector; and determining the information recognition result based on the cosine similarity and a preset similarity threshold.

[0011] Optionally, based on cosine similarity and a preset similarity threshold, the information identification result is determined, including: when there is a change in the air ticket booking information, obtaining the timestamp of the change time, the change operation content and the third biometric information of the user who performs the change operation; based on the timestamp, the change operation content and the third biometric information, generating the booking traceability information; based on the booking traceability information, cosine similarity and a preset similarity threshold, determining the information identification result.

[0012] According to another aspect of an embodiment of the present invention, a security identification device for airport information is also provided, including: a first acquisition module, used to acquire the air ticket booking information of the first user, wherein the air ticket booking information at least includes the first biometric information of the first user; an extraction module, used to perform feature extraction on the first biometric information in the air ticket booking information to obtain a first biometric feature vector; a sending module, used to send the first biometric feature vector to a target airport corresponding to the air ticket booking information; a second acquisition module, used to acquire the second biometric information of the second user in response to the second user arriving at the target airport; and a comparison module, used to compare the second biometric information with the first biometric feature vector to obtain an information identification result, wherein the information identification result is used to indicate whether the second user is the first user.

[0013] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0017] According to another aspect of the embodiments of the present invention, a computer program is further provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0018] In an embodiment of the present invention, a method for securely identifying airport information is provided, including: obtaining air ticket booking information of a first user, wherein the air ticket booking information includes at least first biometric information of the first user; performing feature extraction on the first biometric information in the air ticket booking information to obtain a first biometric feature vector; sending the first biometric feature vector to a target airport corresponding to the air ticket booking information; in response to a second user arriving at the target airport, obtaining second biometric information of the second user; comparing the second biometric information with the first biometric feature vector to obtain an information identification result, wherein the information identification result is used to indicate whether the second user is the first user. It is easy to notice that the present application can obtain the first biometric information of the user when the first user books a ticket, and extract the features of the first biometric information to obtain the first biometric feature vector, so as to realize the timely update of the user's biometric information, and avoid the first user's on-site verification failure due to the failure to update the user's biometric information in time. By extracting the biometric feature vector, fast and accurate identity authentication can be realized, and the efficiency of airport security and other links can be improved. Sending the first biometric feature vector to the target airport corresponding to the ticket booking information can ensure that the passenger's sensitive information can be accessed and used by the appropriate airport, and can ensure that only the target airport related to the first user's itinerary can obtain the first biometric feature vector of the first user, and other unrelated airports have no right to call the first biometric feature vector, which can ensure the security of the user's sensitive information and prevent unauthorized airports or third parties from obtaining the user's biometric information. By sending the first user's biometric feature vector to the target airport, the biometric comparison can be directly performed when the second user arrives at the target airport, which can effectively prevent identity theft and fraud, and improve the accuracy and security of airport information identification. Thus, the technical problem of low efficiency and security in processing and identifying airport information in the related technology is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 is a flow chart of a method for securely identifying airport information according to an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of comparing the efficiency of feature extraction according to an embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of a device for securely identifying airport information according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, 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 "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the present invention, an embodiment of a method for secure identification of airport information is provided. It can be explained that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] Figure 1 is a flow chart of a method for securely identifying airport information according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0027] Step S102, obtaining the air ticket booking information of the first user.

[0028] The air ticket booking information at least includes the first biometric information of the first user.

[0029] The above-mentioned air ticket booking information may refer to the relevant information provided by the passenger when booking an air ticket, which may include but is not limited to: the passenger's personal information: name, ID number, etc.; flight information: flight number, take-off and landing time, cabin, etc.; ticket information: ticket number, seat number, fare, etc.; booking method information: booking channel, purchase time, etc. The air ticket booking information also includes the first biometric information provided by the user during login verification and other processes. The specific air ticket booking information can be determined according to actual needs and is not limited here.

[0030] The above-mentioned first biometric information may refer to the biometric information of the passenger, which is used for biometric verification. Such information may include, but is not limited to: facial feature data obtained through face recognition technology, fingerprint feature data obtained through fingerprint recognition technology, iris feature data obtained through iris recognition technology, voice feature data obtained through voiceprint recognition technology, etc. For example, the first biometric information may include: facial feature data of the passenger, facial information extracted through face recognition technology, which is used for face recognition verification. The first biometric information can be determined according to actual needs and is not limited here.

[0031] In an optional embodiment, when a passenger books a ticket, the system can collect the passenger's ticket booking information, including flight information, seat number, booking time, etc. At the same time, the system can obtain the passenger's biometric information, such as facial information, fingerprint information or iris information. Obtaining the first user's ticket booking information can be achieved in a variety of ways, and can be queried and downloaded through the official website or mobile application of the airline. When purchasing a ticket, the user can provide personal information and contact information, which are stored in the airline's database. The user's ticket booking information can be queried through key information such as the user's name, order number or ID number. By associating the ticket booking information with the biometric information, a more rigorous and secure authentication mechanism can be achieved. For example, when a user goes through check-in, security inspection, boarding and other procedures at the airport, the ticket booking information can be provided and biometric verification can be performed to ensure that the user's identity and itinerary are consistent. This can effectively reduce security risks such as impersonation and theft, and improve the security identification level of airport information. When the first user books a ticket, the user's first biometric information can be obtained, and the user's biometric information can be updated in time, avoiding the first user's on-site verification failure due to the user's biometric information not being updated in time, thereby improving the accuracy and efficiency of the user's biometric information verification and improving the user experience.

[0032] Step S104: extracting features from the first biometric information in the air ticket booking information to obtain a first biometric feature vector.

[0033] In an optional embodiment, the passenger's biometric information, such as fingerprint, iris, face, etc., can first be obtained from the ticket booking system. This information can be provided by the passenger when booking the ticket, and can be obtained through the interface of the ticket system. Then, for the first biometric information obtained, feature extraction processing can be performed, which can include pre-processing the biometric data, such as denoising, enhancement, etc., and then using a specific algorithm to extract the biometric feature vector. The obtained feature vector can be an abstract representation of the biometric feature, which can better describe the uniqueness of the biometric feature. The extracted biometric feature vector can be stored, and can be stored in a database or a specific storage medium. This can facilitate subsequent biometric comparison and verification. In the above process, the obtained biometric feature vector can more accurately describe the passenger's biometric features, thereby improving the accuracy of the biometric system. Biometric technology has a fast recognition speed and can complete the verification of the passenger's identity in a short time. By extracting the biometric feature vector, fast and accurate identity authentication can be achieved, and the efficiency of airport security and other links can be improved.

[0034] Step S106: Send the first biometric feature vector to the target airport corresponding to the air ticket booking information.

[0035] In an optional embodiment, sending the first biometric feature vector to the target airport corresponding to the ticket booking information can ensure that the passenger's sensitive information can be accessed and used by the appropriate airport. The system can search for the corresponding target airport in the pre-set permission control list, which can include departure, transit and destination airport information, and send the first biometric feature vector to the target airport, so that only authorized airports can call the passenger's first biometric feature vector, and unauthorized airports will not be able to obtain or use the first biometric feature vector. In the above process, through permission control and multi-factor evaluation, it is ensured that only authorized airports can access the passenger's sensitive information, effectively preventing information leakage and abuse. The target airport can quickly verify the identity and obtain necessary information when the passenger arrives, improving service efficiency and passenger experience. Sending the first biometric feature vector to the target airport and performing access control through the permission control authorization procedure can effectively protect the security and privacy of passenger information, while improving the efficiency and accuracy of airport services.

[0036] Step S108, in response to the second user arriving at the target airport, obtaining second biometric information of the second user.

[0037] Step S110, comparing the second biometric information with the first biometric feature vector to obtain an information recognition result.

[0038] The information identification result is used to indicate whether the second user is the first user.

[0039] In an optional embodiment, the passenger can be subjected to biometric verification, and the passenger's biometric information, such as fingerprints, facial features, etc., can be collected so as to compare it with the information in the database to confirm its identity. Specifically, when the second user arrives at the target airport, the system can perform biometric verification on the second user, such as providing fingerprint information or performing facial recognition. These biometric information will be recorded to form the second biometric information of the second user, and the system can compare the second biometric information of the second user with the biometric feature vector of the first user. The first biometric feature vector is generated by the biometric information of the first user previously collected and stored in the database, and can be used to uniquely represent the first user. Finally, the system can derive an information identification result based on the comparison result, that is, determine whether the second user is the first user. If the biometric information of the second user matches the biometric feature vector of the first user, then the system will confirm that the second user is the first user. By verifying passengers through biometric technology, identity fraud can be effectively avoided and airport security can be improved. Passengers do not need to carry items such as identification documents or boarding passes. They can complete security checks through biometric verification, which improves the passenger experience. By comparing the second user's biometric information with the first user's biometric feature vector, the passenger's identity security can be effectively ensured, the airport's safety and efficiency can be improved, and the passenger experience can also be improved.

[0040] Optionally, sending the first biometric feature vector to the target airport corresponding to the air ticket booking information includes: parsing the air ticket booking information to obtain user travel information; determining the target airport based on the user travel information, and sending the first biometric feature vector to the target airport.

[0041] In an optional embodiment, when a passenger purchases an air ticket through the air ticket booking system, the system can obtain the passenger's biometric information, such as fingerprints, irises, etc. The biometric information can be converted into a first biometric feature vector and stored in the system. The system can parse the passenger's itinerary information, including the destination airport, based on the air ticket booking information, and send the passenger's first biometric feature vector to the target airport's security identification system. In the above process, only the target airport related to the first user's itinerary can call the passenger's biometric information, ensuring the security and privacy of the passenger's information, which can effectively improve the airport security efficiency and the passenger's travel experience, and ensure the security and privacy of the passenger's information.

[0042] Optionally, sending the first biometric feature vector to the target airport includes: obtaining a preset random initialization vector and an encryption key of a preset encryption algorithm; using a preset encryption algorithm to encrypt the preset random initialization vector, the encryption key and the first biometric feature vector to obtain an encrypted vector; concatenating the preset random initialization vector and the encryption vector to obtain an encrypted data block, and sending the encrypted data block to the target airport; decrypting the encrypted data block based on the target airport to obtain the first biometric feature vector.

[0043] The above-mentioned preset random initialization vector may refer to a random initialization vector generated in advance based on a random function, which may be determined according to actual needs and is not limited here.

[0044] In an optional embodiment, a preset random initialization vector and an encryption key of a preset encryption algorithm may be first obtained. The preset random initialization vector may be a randomly generated initialization vector used to increase the security of the encryption algorithm. The encryption key of the preset encryption algorithm may refer to a key used to encrypt and decrypt data. Then, the preset random initialization vector, the encryption key and the first biometric feature vector may be encrypted using the preset encryption algorithm to obtain an encryption vector, and the preset random initialization vector and the encryption key may be encrypted with the first biometric feature vector to ensure the security of the data. Then, the preset random initialization vector and the encryption vector may be spliced ​​to obtain an encrypted data block, and the encrypted data block may be sent to the target airport, and the encrypted data block may be sent to the target airport so that the target airport may perform a decryption operation. Finally, the encrypted data block may be decrypted based on the target airport to obtain the first biometric feature vector. The target airport may use the same preset encryption algorithm and encryption key to decrypt the encrypted data block, thereby restoring the original first biometric feature vector. By encrypting and decrypting data using the preset encryption algorithm and encryption key, the security of the data may be effectively protected to prevent the data from being stolen or tampered with during transmission. By encrypting the first biometric feature vector, the user's privacy data can be effectively protected to ensure that the user's biometric information is not leaked.

[0045] Optionally, the encrypted data block is decrypted based on the target airport to obtain a first biometric feature vector, including: decrypting the encryption vector in the encrypted data block based on the target airport to obtain a decrypted biometric feature vector and a decrypted random initialization vector; comparing the decrypted random initialization vector with a preset random initialization vector in the encrypted data block to obtain a comparison result, wherein the comparison result is used to characterize whether the decrypted random initialization vector and the preset random initialization vector are consistent; and determining the first biometric feature vector based on the comparison result and the decrypted biometric feature vector.

[0046] In an optional embodiment, first, the target airport can receive an encrypted data block, which includes an encryption vector and a biometric feature vector. The target airport can first use the corresponding key to decrypt the encrypted data block to obtain a decrypted biometric feature vector and a decrypted random initialization vector. The decrypted random initialization vector is the decryption result of the initialization vector used in the encryption operation. Then, the target airport can compare the decrypted random initialization vector with the random initialization vector preset in the encrypted data block. The comparison can determine whether the decrypted random initialization vector is consistent with the preset random initialization vector. The accuracy and integrity of the decryption operation can be ensured. When the two random initialization vectors are consistent, it can be determined that the decryption operation is correct and the encrypted data block has not been tampered with during the transmission process. Finally, the target airport can determine the first biometric feature vector based on the comparison result and the decrypted biometric feature vector. By combining the comparison result and the biometric feature vector, the target airport can determine the final biometric feature vector for subsequent biometric verification and identification operations. In the above process, by comparing the decrypted random initialization vector with the preset random initialization vector, the accuracy of the decryption operation can be detected, biometric failure caused by data decryption errors can be avoided, and the final biometric feature vector can be ensured to be accurate, thereby improving the recognition accuracy and security of the biometric system, effectively avoiding the leakage and tampering of biometric data, and ensuring the secure identification of airport information.

[0047] Optionally, the second biometric information is compared with the first biometric feature vector to obtain an information recognition result, including: extracting features from the second biometric information to obtain a second biometric feature vector; determining the cosine similarity between the second biometric feature vector and the first biometric feature vector; and determining the information recognition result based on the cosine similarity and a preset similarity threshold.

[0048] In an optional embodiment, the second biometric information can first be feature extracted to obtain a second biometric feature vector, which can be achieved through various biometric technologies, such as fingerprint recognition, face recognition, iris recognition, etc. By extracting the features of the second biometric information, it can be converted into a feature vector, which is convenient for subsequent comparison and analysis. Then, the cosine similarity between the second biometric feature vector and the first biometric feature vector can be determined. Calculating the cosine similarity can help determine the similarity between the second biometric information and the first biometric information, so as to perform the next step of judgment and processing. Finally, the information recognition result can be determined based on the cosine similarity and the preset similarity threshold. In this step, a preset similarity threshold can be set to determine whether the similarity between the second biometric information and the first biometric information meets the requirements. In the above process, by extracting the features and comparing the similarity of the biometric information, the accuracy and reliability of information recognition can be improved. Setting a preset similarity threshold can help screen and judge in the matching process, improve the matching efficiency and speed, and thus improve the level and efficiency of airport security management.

[0049] Optionally, based on cosine similarity and a preset similarity threshold, the information identification result is determined, including: when there is a change in the air ticket booking information, obtaining the timestamp of the change time, the change operation content and the third biometric information of the user who performs the change operation; based on the timestamp, the change operation content and the third biometric information, generating the booking traceability information; based on the booking traceability information, cosine similarity and a preset similarity threshold, determining the information identification result.

[0050] In an optional embodiment, when the ticket booking information is changed, the system can record the timestamp of the change, including the date and time. At the same time, the system can record the specific operation content of the change, such as modifying the passenger name, seat number and other information. The system can also record the third biometric information of the user who performs the change operation. Then, the system can generate the booking traceability information based on the timestamp, the change operation content and the third biometric information. The booking traceability information may include various operation records during the booking process and the ticket change process, including specific information of the booking, payment, verification and other links, so as to facilitate subsequent traceability analysis. Finally, the system can determine the information recognition result based on the booking traceability information, cosine similarity and preset similarity threshold. The system can compare the current information with the historical information, calculate the cosine similarity, and compare it with the preset similarity threshold. Through the above process, it can ensure that the security identification process of airport information is more accurate and reliable. The system can promptly detect and record changes in information. At the same time, by comparing the cosine similarity with the preset similarity threshold, it can effectively determine whether the information has been tampered with, which can bring higher information security and reliability, effectively prevent information leakage and tampering, and improve the efficiency and security of airport information management. By constructing the user's ticket booking traceability information, this application can better trace and monitor the user's operating behavior in the system, reduce the risk of information leakage and illegal access, and improve information security. By tracing the user's ticket booking operation process, it can promptly discover operational anomalies and errors, improve the system's operating efficiency and stability, and reduce the risk of system failure and data loss. Ticket booking traceability information can help the system better understand user needs and preferences, provide personalized services and recommendations, and improve user experience and satisfaction. Setting up the construction of the user's ticket booking traceability information in the field of airport information security identification can improve information security, strengthen user identity authentication, optimize system operating efficiency and improve user experience.

[0051] The technical solution proposed in this application is described below in combination with an optional embodiment. This application proposes a blockchain-driven airport sensitive information security identification application method, which involves the field of blockchain smart contract sensitive information security identification. This method uses the characteristics of blockchain technology such as decentralization, immutability, transparency and traceability to conduct comprehensive security management and identification of airport sensitive information. By building a sensitive information storage and transmission system based on blockchain, real-time monitoring, secure storage and rapid identification of sensitive information can be achieved. At the same time, combined with cryptography technology and smart contracts and other technologies, the security and reliability of the system are improved. The biometric data features are aggregated and stored on the blockchain, and identity authentication is performed in the form of smart contracts, which effectively prevents the user's sensitive data from being illegally accessed or tampered with by attackers, while ensuring the immutability and traceability of operation records in the user's biometric data storage and use process.

[0052] This application designs a method to realize the function of bioinformatics data feature aggregation and storage, including the extraction, aggregation and storage of bioinformatics data features, as well as permission control and dynamic management and optimization. Construct a bioinformatics data feature extraction algorithm to distinguish sensitive information from non-sensitive information, extract and encrypt sensitive information features, and aggregate and store them with non-sensitive information on the blockchain network and cloud servers. Rely on the characteristics of smart contracts to implement complex permission control of the role-based access control (RBAC) model and limit the call of sensitive information.

[0053] This application designs a method for fusion and extraction of biometric data features for passenger identity verification, which mainly includes the following steps: passenger biometric information collection, which can be divided into active collection and passive collection. Active collection can refer to passengers voluntarily uploading biometric information such as pictures, and the system will pre-process the uploaded information; passive collection can refer to when passengers pass by scene equipment, and the equipment automatically captures and processes biometric information. Sensitive data accurate perception, for the collected data, this application accurately distinguishes sensitive data D sensitive and non-sensitive data D non-sensitive Sensitive information is information closely related to the privacy of the passenger, and non-sensitive information is other information. This application mainly uses fixed data format, structured data, and then automatically marks sensitive information and non-sensitive information in the unified format. Data preprocessing can extract the characteristic information of passenger sensitive information based on artificial intelligence algorithms, and generate a high-dimensional vector F={f1,f2,...,f n}, for subsequent information storage and processing. Sensitive information encryption, you can use Advanced Encryption Standard (AES) encryption technology to store sensitive information, ensuring that sensitive data is only decrypted and accessed when necessary to meet the requirements of data protection regulations. Authentication and identification, the system determines the identity of the passenger by comparing the fused feature vector with the stored features in the database. The system has fast recognition and adaptive matching capabilities to maintain efficient verification in multi-person and complex environments. This module can be applied to scenarios such as airport boarding gate verification, self-service check-in, security checks, etc. to ensure efficient operation in different scenarios.

[0054] This application establishes a multi-domain, multi-level data RBAC model for the overall scenario design, implements dynamic management and optimization of permissions based on smart contracts, implements access control to resources, and ensures the security and controllability of sensitive data. First, define roles. Define three roles in the entire field, R = {R1, R2, R3}, respectively R1: super administrator, R2: administrator and R3: ordinary user, and define three permissions in the entire field, P = {P1, P2, P3}, respectively P1: can modify the list of administrators and ordinary users, P2: can access information storage services, P3: can access information matching services. The mapping relationship between roles and permissions is as follows: Super administrator R1 → {P1, P2, P3}, has all permissions; Administrator R2 → {P2, P3}, can access information storage and information matching services; Ordinary user R3 → {P3}, can access information matching services. The mapping relationship M is as follows: M:R×P→{0,1}, where M(r,p)=1 means that role r has permission p, and M(r,p)=0 means that role r does not have permission p. After defining the roles and permissions of the entire domain, different users can be assigned corresponding roles in different domains. In domain α, roles used in role policy R can be assigned. In this domain, roles can be matched with permissions in permission policy P to obtain system support services. In addition, if the roles and permissions involved in the domain require more detailed division, roles R and permissions P can be dynamically updated to achieve complex permission control. When user U requests access to operation A, the user's role r must first be determined: r=roles(U). Then, it is verified whether the user has permission to perform the operation, CheckPermission(U,A)=M(r,p). If the result is 1, the user has permission to access, otherwise access is denied. If the permission verification passes, the data access operation is executed, Access(U,A)=Execute(A). After each access operation, a log record will be generated, Log(U,A,result,t), where result is the execution result and t is the timestamp for subsequent data tracing. When permissions need to be adjusted dynamically, this can be achieved by updating the mapping relationship M between roles and permissions.

[0055] In addition, this application adopts different hierarchical access strategies for sensitive data and non-sensitive data. sensitive and non-sensitive data D non-sensitive The access is defined, which will be fully reflected in the permission policy P. When user U uses functions such as access to data storage and data services, the validity of the permissions for the data level D is confirmed.

[0056]

[0057] Among them, U is the user, A is the requested operation. M(r,p) is the permission control, f(A U,A D ) is a matching function between user attributes and data attributes. This function needs to additionally determine whether the user meets the attributes required to access the data. The data is defined as sensitive data D sensitive and non-sensitive data D non-sensitive , when the user meets the access definition, f(A U ,A D ) returns 1, otherwise 0. When all conditions are met, the Valid function returns 1, and user U can access successfully.

[0058] This application proposes a blockchain-based intelligent computing technology for sensitive information on the chain, including a blockchain network, a smart contract module, an encryption and decryption module, and an intelligent computing processing module. The blockchain network is mainly used to store sensitive information and smart contracts. The smart contract module contains multiple smart contracts for defining access control rules and data processing logic for sensitive information. The encryption and decryption module uses the AES (256)-Galois / Counter Mode (GCM) encryption algorithm based on a counter to encrypt and decrypt sensitive information to ensure the security of data during transmission and storage. The intelligent computing processing module implements the use of deep learning face recognition algorithms on the blockchain, performs computational processing on faces in sensitive information, and ensures excellent recognition results while having extremely high security.

[0059] Under the premise of ensuring the normal flow of data, due to the transparency and openness of blockchain data, some data needs to be encrypted, and in the process of data circulation, sensitive data is also required to be encrypted to achieve a certain degree of security. This application adds encryption and decryption modules to the data transmission and storage parts of the blockchain, and will perform adaptive processing on sensitive information and non-sensitive information with distinction, which can not only improve performance, but also improve efficiency. This application classifies data to distinguish sensitive data D sensitive and non-sensitive data D non-sensitive After receiving the data, the system first distinguishes the data level and takes encryption measures according to the data level. non-sensitive No encryption measures are taken and the data is stored locally. sensitive After basic processing, the AES encryption strategy is adopted to encrypt the data D s ′ ensitive After the data arrives from the previous end to the next end, the next end will adaptively determine the level of the received data and distinguish sensitive data D sensitive and non-sensitive data D non-sensitive After that, the encrypted data D is processed by the latter end using the data carrying information and decryption strategy s′ ensitive Decryption and authentication are performed. After authentication, the data enters the overall logical process of the system. After the latter end has finished using the data, when sending it to the next end, the same adaptive encryption and decryption strategy is adopted, and different methods are adopted for hierarchical data to ensure data security. The adaptive encryption and decryption mechanism of data runs through the system and is reflected in the data flow. A modular approach is adopted to optimize execution efficiency and improve the overall stability and security of the system.

[0060] This step uses the AES (256)-GCM encryption algorithm for corresponding encryption. The encryption logic is as follows: C = AES-GCM (K, IV, P), where C is the ciphertext, including the encrypted data and the GCM tag, K is the AES key (256 bits), IV is a randomly generated initialization vector (Nonce, 12 bytes), and P is the plaintext. In order to maintain the security and randomness of the encryption process, IV can be transmitted together with the ciphertext to ensure that the original data can be correctly restored during decryption. The initialization vector IV and the ciphertext C are concatenated to output the data block D = IV∥C. Finally, in order to be more suitable for transmission on different platforms and in different languages, E = Base64 (D), and the data block D is Base64 encoded to obtain the output E. The decryption logic has a similar logic to the encryption logic in reverse, as follows: Base64 decrypt the data input E, D = Base64 -1 (E), get the data block D, which will contain the initialization vector IV and ciphertext C. Extract the data block D, IV = D[0:12], C = D[12:], get the initialization vector IV and ciphertext C. Finally, decrypt the ciphertext, P = AES-GCM -1 (K, IV, C), get the plaintext P.

[0061] This method combines the security features of blockchain to achieve intelligent face recognition on the chain, providing protection for the safe use of sensitive data. After this method collects the original face data D, it first uses an artificial intelligence algorithm to extract the face feature value D face =F(D), which can effectively increase the system efficiency. Then the eigenvalue is encrypted using the AES(256)-GCM algorithm, i.e., C face =AES-GCM(K,IV,D face ), where C face is the encrypted ciphertext data, the encrypted data C face Upload to the blockchain node. This step ensures the security of data during transmission and storage, and avoids data leakage. Combined with the permission control in this application, roles in different usage domains can be assigned cross-domain data usage permissions. The cross-domain permission P can be defined as the classification of sensitive data D for passenger information. sensitive Or non-sensitive data D non-sensitiveThe access, storage, matching and other services of domain a can be mainly defined as the face recognition service P1 in the passenger sensitive information. a and role R using domain b b Assign the permission P1, and when a specific user uses it, assign the role of the user's domain to achieve cross-domain service access and permission control for different users, that is, the mapping relationship M(R a ,P1)=1,M(R b ,P1)=1. In addition, the flexible permission allocation definition and strategy effectively improve the overall efficiency of this method. In the subsequent specific face recognition service, the system will call the feature extraction algorithm F() to extract the newly acquired face data feature vector C1 ff , and the feature vector C stored on the blockchain ff Perform cosine similarity comparison, that is In this method, if CosineSim(C ff ,C1 ff ) is less than 0.09, it is considered to be the feature vector of the same person and the face recognition is considered passed, otherwise it is considered failed. Experiments have shown that compared with the operation time of uploading facial feature information and uploading complete facial information to the blockchain, the facial recognition operation of this method only takes 52 microseconds on average, which has a higher execution efficiency advantage.

[0062] This application designs a function of sensitive information data fingerprint generation and traceability. In order to improve data credibility and strengthen data security, a unique data fingerprint is generated by calling a data fingerprint generation algorithm for sensitive information to verify the authenticity of the data and prevent tampering. In order to clarify the source and use process of the data, a real-time sensitive data monitoring structure is deployed, a specific filter is constructed to obtain the sensitive information usage records involved, and based on the unique identification of the data, a unique fingerprint chain is generated for the data to form a core strategy for tracing the operation records, thereby establishing a complete traceability mechanism and system. The key components are mainly divided into three parts, namely the fingerprint generation module, the blockchain layer and the smart contract. The fingerprint generation module generates a unique data fingerprint for the original data and adds metadata. The blockchain layer stores fingerprints and their operation records in a decentralized manner to ensure the immutability of the data. The smart contract manages the generation, storage and verification of data fingerprints. To generate data fingerprints, it is first necessary to perform encrypted hash H1() processing on the required data D as a preliminary fingerprint: FP1 = H1(D) to ensure the consistency of the input data. The preliminary fingerprint is then combined with additional metadata, which may include timestamps, data source IDs, operation types, etc., and encrypted again: FP=H2(FP1∥T∥ID∥O), where T represents the current timestamp, which is used to record the time when the data was generated. ID represents the ID that uniquely identifies the source of the data. O represents the operation type, which refers to the specific operation performed on the data. Ultimately, the fingerprint FP will contain the following information FP=H2(H1(D)∥T∥ID∥O), which not only ensures that each fingerprint is unique, but also contains rich contextual information to facilitate subsequent operation traceability. Use smart contracts to store fingerprints and metadata on the blockchain to ensure that they cannot be tampered with: Store(FP,T,ID,O)→Block n When the data is at a certain time T n When updated, a new fingerprint FP is generated n ,The new fingerprint is generated based on the unique identification data ID, operation type, timestamp and metadata, FP n =H(D n ∥T n ∥ID n ∥O n ). Where D n is the current data state, T n Represents the timestamp of the operation, ID n Represents the unique identifier of the initial data, O nIndicates the type of operation. Each newly generated fingerprint will be stored in the blockchain, relying on the unique identification data ID to form a fingerprint chain. By recording the relationship between fingerprints, each operation can be easily tracked to form a complete operation traceability chain. Each data fingerprint in the operation is linked to other fingerprints by ID. Therefore, any tampering of an operation in the operation chain will be automatically recorded by the system, so that the tampering behavior can be detected.

[0063] Specifically, when passengers make a reservation through the booking system, they upload personal information, or upload information through other channels, including sensitive information such as facial information, as well as other non-sensitive information such as flight, date, and airport. The passenger's sensitive information will be intelligently identified and distinguished by the biometric data feature extraction algorithm, and encrypted using the AES (256)-GCM encryption algorithm and added to the blockchain for storage. The remaining non-sensitive information is encrypted and stored locally. The system uses the data fingerprint generation algorithm to generate a unique data fingerprint based on the passenger's sensitive information, and stores it on the blockchain to verify the authenticity of the data, prevent tampering, and support traceability. Based on the relevant information uploaded by the passenger, the itinerary involves airports, and the corresponding airport is authorized to access the passenger's sensitive information through the authorization procedure of biometric data access rights control based on the RBAC model, so that the authorized airport has the authority to call the passenger's sensitive information, and the unauthorized airport cannot call the passenger's sensitive information. The validity of the airport's authority is evaluated using multiple factors. When passengers arrive at the airport, face recognition is used for security checks and other operations. After receiving the passenger's facial information, the application calls the passenger's facial data features for efficient cross-domain retrieval. In different usage domains, passenger information is quickly extracted, and the identity of the security personnel is determined after comparing the feature values. The addition, authorization and call operations of sensitive information will be recorded and saved on the blockchain, and the fingerprint chain will be used to ensure that the data cannot be tampered with, while supporting data traceability. The airport or user end can trace the use records of sensitive information through the application interface, starting from the addition of data, and querying each authorization and call record of sensitive data. The user will eventually receive status feedback provided by the system, informing the user whether the operation is successful, and providing necessary suggestions and follow-up steps.

[0064] In this application, blockchain technology, with its decentralized, tamper-proof and full-process traceability characteristics, significantly improves the security of airport sensitive information. Applying blockchain technology to airport scenarios effectively combines face recognition technology and its applications, properly preserves sensitive passenger information such as face and personnel information, and ensures the security of sensitive information use and transmission. Storing and transmitting sensitive information through blockchain can effectively prevent data from being tampered with, stolen or deleted, thereby protecting the privacy and security of passengers and airports. Designing and using the permission control technology of blockchain smart contracts, defining and executing the rules of permission management and access control on the blockchain to implement complex permission logic and access control strategies can effectively ensure data security, promote compliance, improve efficiency and user experience. Blockchain technology can ensure that data cannot be tampered with once it is on the chain. By recording each call to the blockchain data, a data fingerprint is generated to form a fingerprint chain, ensuring that the use status of sensitive data can be traced and prevented from being tampered with. The sensitive data on the blockchain is encrypted by an encryption algorithm and the data is stored securely. It is supervised by the administrator with the highest authority to always maintain data consistency. The application uses machine learning to identify facial data and combines it with blockchain technology. It not only has efficient facial recognition capabilities but also has high data security.

[0065] Figure 2 is a schematic diagram of comparing the efficiency of feature extraction according to an embodiment of the present invention, such as Figure 2 As shown in the figure, the horizontal axis represents the number of tests, and the vertical axis represents time (ms). In the figure, ① represents the curve in which no feature extraction is performed on the user's biometric information, and the user identity authentication is performed based on the cloud server, and the average time consumption is 6.06ms; ② represents the curve in which feature extraction is performed on the user's biometric information, and the user identity authentication is performed based on the cloud server, and the average time consumption is 3.36ms; ③ represents the curve proposed in the present application in which feature extraction is performed on the user's biometric information, and the user identity authentication is performed based on the target airport terminal, and the average time consumption is 0.052ms. It can be seen that the technical solution proposed in the present application has a higher execution efficiency advantage.

[0066] According to another aspect of an embodiment of the present application, a device for secure identification of airport information is also provided. The device can execute the method for secure identification of airport information of the above embodiment. The specific implementation method and preferred application scenario are the same as those of the above embodiment and will not be repeated here.

[0067] Figure 3 is a schematic diagram of a security identification device for airport information according to an embodiment of the present application, such as Figure 3 As shown, the device includes the following: a first acquisition module 302 , an extraction module 304 , a sending module 306 , a second acquisition module 308 and a comparison module 310 .

[0068] Among them, the first acquisition module is used to obtain the air ticket booking information of the first user, wherein the air ticket booking information at least includes the first biometric information of the first user; the extraction module is used to extract features from the first biometric information in the air ticket booking information to obtain a first biometric feature vector; the sending module is used to send the first biometric feature vector to the target airport corresponding to the air ticket booking information; the second acquisition module is used to obtain the second biometric information of the second user in response to the second user arriving at the target airport; the comparison module is used to compare the second biometric information with the first biometric feature vector to obtain an information recognition result, wherein the information recognition result is used to indicate whether the second user is the first user.

[0069] Among them, the sending module is also used to parse the air ticket booking information to obtain the user's itinerary information; determine the target airport based on the user's itinerary information, and send the first biometric feature vector to the target airport.

[0070] Among them, the sending module is also used to obtain a preset random initialization vector and an encryption key of a preset encryption algorithm; use the preset encryption algorithm to encrypt the preset random initialization vector, the encryption key and the first biometric feature vector to obtain an encryption vector; concatenate the preset random initialization vector and the encryption vector to obtain an encrypted data block, and send the encrypted data block to the target airport; decrypt the encrypted data block based on the target airport to obtain the first biometric feature vector.

[0071] Among them, the sending module is also used to decrypt the encryption vector in the encrypted data block based on the target airport to obtain a decrypted biometric feature vector and a decrypted random initialization vector; compare the decrypted random initialization vector with the preset random initialization vector in the encrypted data block to obtain a comparison result, wherein the comparison result is used to characterize whether the decrypted random initialization vector and the preset random initialization vector are consistent; based on the comparison result and the decrypted biometric feature vector, determine the first biometric feature vector.

[0072] Among them, the comparison module is also used to extract features from the second biometric information to obtain a second biometric feature vector; determine the cosine similarity between the second biometric feature vector and the first biometric feature vector; and determine the information recognition result based on the cosine similarity and a preset similarity threshold.

[0073] Among them, the comparison module is also used to obtain the timestamp of the change time, the change operation content and the third biometric information of the user who performs the change operation when there is a change in the air ticket booking information; generate the ticket tracing information based on the timestamp, the change operation content and the third biometric information; determine the information recognition result based on the ticket tracing information, cosine similarity and a preset similarity threshold.

[0074] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0075] The above-mentioned memory may refer to a device inside a computer for storing data and programs, and may include memory, hard disk, etc., wherein the memory may be used to temporarily store running programs and data, the hard disk may be used to store programs and data for a long time, and the memory may be used to enable the computer to read and write data, and execute programs; the above-mentioned processor may be responsible for executing instructions in computer programs and performing data processing, and may be responsible for controlling and executing various operations, including arithmetic operations, logical operations, data transmission, etc.

[0076] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0077] The above-mentioned computer storage medium may refer to a medium in a computer memory used to store certain discontinuous physical quantities. Computer storage media mainly include semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc.; the stored program included in the computer-readable storage medium may be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0078] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0079] The above-mentioned computer program product may refer to a software program that has been written, tested and released and can be run on a computer or other device. The computer program product may include an application, an operating system, tool software, etc., which is used to implement specific functions or solve specific problems.

[0080] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0081] The above-mentioned non-volatile computer-readable storage medium may refer to a medium for storing data. The non-volatile computer-readable storage medium can keep the data from being lost when the power is off, and can be used to store long-term data, such as operating systems, applications, and user files. The non-volatile storage medium may include hard disk drives, solid-state drives, optical disks, and flash memory storage devices, etc.

[0082] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0083] The above-mentioned computer program may refer to a collection of instructions used to tell a computer to perform a specific task or operation. A computer program may be written by a programmer using a specific programming language and may include algorithms, data structures, logic, and control flows. A computer program may be used for a variety of purposes, including application software, operating systems, and the like.

[0084] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0085] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0086] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0087] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0088] 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 storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0089] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for securely identifying airport information, characterized in that: include: Acquire the air ticket booking information of the first user, wherein the air ticket booking information at least includes the first biometric identification information of the first user; Extracting features of the first biometric information in the air ticket booking information to obtain a first biometric feature vector; Sending the first biometric feature vector to the target airport corresponding to the air ticket booking information; In response to a second user arriving at the target airport, acquiring second biometric information of the second user; The second biometric information is compared with the first biometric feature vector to obtain an information recognition result, wherein the information recognition result is used to indicate whether the second user is the first user.

2. The method for securely identifying airport information according to claim 1, characterized in that: Sending the first biometric feature vector to a target airport corresponding to the air ticket booking information includes: Parsing the air ticket booking information to obtain user itinerary information; A target airport is determined based on the user travel information, and the first biometric feature vector is sent to the target airport.

3. The method for securely identifying airport information according to claim 2, characterized in that: Sending the first biometric feature vector to the target airport includes: Obtaining a preset random initialization vector and an encryption key of a preset encryption algorithm; Using the preset encryption algorithm, encrypt the preset random initialization vector, the encryption key and the first biometric feature vector to obtain an encrypted vector; Concatenate the preset random initialization vector and the encryption vector to obtain an encrypted data block, and send the encrypted data block to the target airport; The encrypted data block is decrypted based on the target airport to obtain the first biometric feature vector.

4. The method for securely identifying airport information according to claim 3, characterized in that: Decrypting the encrypted data block based on the target airport to obtain the first biometric feature vector includes: Decrypting the encrypted vector in the encrypted data block based on the target airport to obtain a decrypted biometric feature vector and a decrypted random initialization vector; Comparing the decrypted random initialization vector with the preset random initialization vector in the encrypted data block to obtain a comparison result, wherein the comparison result is used to indicate whether the decrypted random initialization vector is consistent with the preset random initialization vector; Based on the comparison result and the decrypted biometric feature vector, the first biometric feature vector is determined.

5. The method for securely identifying airport information according to claim 1, characterized in that: Comparing the second biometric identification information with the first biometric identification feature vector to obtain an information identification result includes: Extracting features from the second biometric information to obtain a second biometric feature vector; determining a cosine similarity between the second biometric feature vector and the first biometric feature vector; The information recognition result is determined based on the cosine similarity and a preset similarity threshold.

6. The method for securely identifying airport information according to claim 5, characterized in that: Determining the information recognition result based on the cosine similarity and a preset similarity threshold includes: If there is any change in the air ticket booking information, obtaining a timestamp of the change time, the change operation content, and the third biometric identification information of the user who performs the change operation; Generate ticket booking tracing information based on the timestamp, the change operation content and the third biometric information; The information recognition result is determined based on the ticket booking tracing information, the cosine similarity and the preset similarity threshold.

7. A security identification device for airport information, characterized in that: include: A first acquisition module, configured to acquire the ticket booking information of the first user, wherein the ticket booking information at least includes the first biometric identification information of the first user; An extraction module, configured to extract features from the first biometric information in the air ticket booking information to obtain a first biometric feature vector; A sending module, used for sending the first biometric feature vector to a target airport corresponding to the air ticket booking information; a second acquisition module, configured to acquire second biometric identification information of the second user in response to the second user arriving at the target airport; A comparison module is used to compare the second biometric information with the first biometric feature vector to obtain an information recognition result, wherein the information recognition result is used to indicate whether the second user is the first user.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein the program, when running, executes the method for securely identifying airport information as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the method for securely identifying airport information according to any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method for securely identifying airport information according to any one of claims 1 to 6.

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