Rail transit vehicle maintenance strategy optimization method and system based on homomorphic encryption

Abstract

The invention discloses a rail transit vehicle maintenance strategy optimization method and system based on homomorphic encryption, and relates to the technical field of strategy optimization, and the method specifically comprises the steps: receiving a name of a to-be-used encryption algorithm and a to-be-encrypted data list; calling an encryption algorithm and to-be-encrypted data; generating a public key and a private key according to an encryption algorithm; encrypting the to-be-encrypted data by using the public key to generate first encrypted data; calculating an encryption calculation result according to the first encryption data; decrypting the encrypted calculation result by using a private key to obtain a real calculation result; performing transformation processing on the real calculation result to generate transformation data; and transmitting the transformation data to the second platform, and optimizing a vehicle maintenance strategy according to the transformation data. According to the method, the data can participate in the analysis process of the rail transit vehicle on the premise of not exposing core confidential data of an enterprise, and scientific data support is provided for design and maintenance strategies of the rail transit vehicle by technicians.

Description

Technical Field

[0001] The present invention relates to the technical field of strategy optimization, and more specifically to a rail transit vehicle maintenance strategy optimization method and system based on homomorphic encryption. Background Art

[0002] With the rapid development of the rail transit industry, the optimization of vehicle maintenance strategies has become particularly important. Reasonable maintenance strategies can not only extend the service life of vehicles and improve operating efficiency, but also effectively reduce operating costs and enhance the market competitiveness of enterprises. However, in the process of formulating and implementing these strategies, enterprises are faced with the problem of how to balance economic benefits and information security. In particular, the cost analysis data in the maintenance strategy often contains the company's core business secrets, which requires enterprises to take strict protection measures when using these data.

[0003] Among them, economic analysis is a key component of optimizing rail transit vehicle maintenance strategies. It helps decision makers determine the optimization direction of vehicle maintenance strategies and vehicle design. This analysis usually involves a large amount of financial data, including but not limited to material costs, labor costs, maintenance costs, and preventive maintenance costs. Accurate economic analysis results are crucial to ensuring the efficiency and economy of maintenance work.

[0004] However, although economic analysis is extremely important for optimizing maintenance strategies, the management of related sensitive data has brought considerable challenges to enterprises. On the one hand, in order to ensure data security, enterprises usually limit data access rights, which may cause obstacles for design teams when conducting necessary analysis. On the other hand, overly strict access control may also affect the efficiency of collaboration between teams and even hinder the development of innovative thinking.

[0005] Therefore, how to effectively analyze data and promote the optimization of maintenance strategies while ensuring data security is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0006] In view of this, the present invention provides a rail transit vehicle maintenance strategy optimization method and system based on homomorphic encryption, which overcomes the above-mentioned defects.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A rail transit vehicle maintenance strategy optimization method based on homomorphic encryption, the specific steps are:

[0009] Encryption process:

[0010] The first platform receives the name of the encryption algorithm to be used and the list of data to be encrypted;

[0011] Calling an encryption algorithm according to the name of the encryption algorithm to be used, and extracting the data to be encrypted according to the list of data to be encrypted;

[0012] Generate a public key and a private key according to the encryption algorithm;

[0013] Encrypting the data to be encrypted using the public key to generate first encrypted data;

[0014] Sending the first encrypted data and the public key to the second platform, and receiving the encryption calculation result sent by the second platform;

[0015] Decryption process:

[0016] The first platform receives the encrypted calculation result, and decrypts the encrypted calculation result using the private key to obtain a real calculation result;

[0017] Performing transformation processing on the real calculation result to generate transformation data;

[0018] The transformed data is transmitted to the second platform, and the vehicle maintenance strategy is optimized according to the transformed data.

[0019] Optionally, the steps for obtaining the name of the encryption algorithm to be used and the list of data to be encrypted are:

[0020] Construct vehicle maintenance analysis model according to demand objectives;

[0021] generating the data list to be encrypted according to the vehicle maintenance model;

[0022] The name of the encryption algorithm to be used is determined according to the list of data to be encrypted.

[0023] Optionally, the vehicle maintenance analysis model is expressed as:

[0024] LSC=LSC cm +LSC pm =N cm (H cm *C labor +C part )+N pm1 (H pm1 *C labor +

[0025] η*C part )+N pm2 (H pm2 *C labor +C part );

[0026] In the formula, LSCcm To repair the maintenance sub-model; LSC pm N is the preventive maintenance submodel; cm H is the number of repair and maintenance times; cm Repair and maintenance hours; C labor C is the unit labor time fee; part is the component price; N pm1 The number of maintenance times for preventive disassembly and overhaul; H pm1 is the maintenance man-hours for preventive disassembly and overhaul; η is the proportion of material costs for preventive disassembly and overhaul; N pm2 Number of maintenance to prevent replacement; H pm2 Maintenance hours for preventive replacement.

[0027] Optionally, the list of data to be encrypted includes unit labor costs, prices of spare parts and consumables required for repair and maintenance, and prices of spare parts and consumables required for preventive maintenance.

[0028] Optionally, the step of obtaining the encryption calculation result is:

[0029] receiving the first encrypted data and the public key;

[0030] Using the public key to encrypt the data to be calculated, to obtain second encrypted data;

[0031] Substituting the first encrypted data and the second encrypted data into the vehicle maintenance analysis model to obtain the encrypted calculation result.

[0032] Optionally, the transformation processing is a desensitization processing or a conversion calculation.

[0033] A rail transit vehicle maintenance strategy optimization system based on homomorphic encryption, comprising:

[0034] A data receiving module, used for receiving the name of the encryption algorithm to be used and the list of data to be encrypted;

[0035] A data extraction module, used to call the encryption algorithm according to the name of the encryption algorithm to be used, and extract the data to be encrypted according to the list of data to be encrypted;

[0036] A key generation module, used to generate a public key and a private key according to the encryption algorithm;

[0037] An encryption processing module, used to encrypt the data to be encrypted using the public key to generate first encrypted data;

[0038] A first data exchange module, used to send the first encrypted data and the public key to the second platform, and receive the encryption calculation result sent by the second platform;

[0039] A decryption processing module, used to receive the encrypted calculation result, and use the private key to decrypt the encrypted calculation result to obtain a real calculation result;

[0040] A data transformation module performs transformation processing on the real calculation result to generate transformation data;

[0041] A second data exchange module, used for sending the transformed data to the second platform;

[0042] A strategy optimization module is used to optimize the vehicle maintenance strategy according to the transformed data.

[0043] Optionally, it also includes:

[0044] A model building module is used to build a vehicle maintenance analysis model according to demand objectives;

[0045] A data screening module, used for generating the data list to be encrypted according to the vehicle maintenance model;

[0046] The algorithm selection module is used to determine the name of the encryption algorithm to be used according to the list of data to be encrypted.

[0047] It can be seen from the above technical solutions that the present invention discloses a rail transit vehicle maintenance strategy optimization method and system based on homomorphic encryption, which has the following beneficial effects compared with the prior art:

[0048] 1. The present invention can safely store and transmit sensitive data by using homomorphic encryption, ensuring that the data will not be illegally accessed even in an untrusted environment;

[0049] 2. The present invention can complete the calculation without decryption, thus improving the processing speed;

[0050] 3. The present invention can make these data participate in the analysis process of rail transit vehicles without revealing the core confidential data of the enterprise, give full play to the potential value of the data, provide scientific data support for the design and maintenance strategies of rail transit vehicles by technicians, enhance the market competitiveness of vehicle products, and create higher value for the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0052] Figure 1The present invention provides a flow chart of the method. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0054] On the one hand, the present invention discloses a rail transit vehicle maintenance strategy optimization method based on homomorphic encryption, such as Figure 1 As shown, the specific steps are:

[0055] Encryption process:

[0056] The first platform receives the name of the encryption algorithm to be used and the list of data to be encrypted;

[0057] Call the encryption algorithm according to the name of the encryption algorithm to be used, and extract the data to be encrypted according to the data list to be encrypted;

[0058] Generate public key and private key according to encryption algorithm;

[0059] Encrypting the data to be encrypted using the public key to generate first encrypted data;

[0060] Sending the first encrypted data and the public key to the second platform, and receiving the encryption calculation result sent by the second platform;

[0061] Decryption process:

[0062] The first platform receives the encrypted calculation result, and decrypts the encrypted calculation result using the private key to obtain the real calculation result;

[0063] Perform transformation processing on the real calculation results to generate transformation data;

[0064] The transformed data is transmitted to the second platform, and the vehicle maintenance strategy is optimized according to the transformed data.

[0065] In one embodiment, the steps for obtaining the name of the encryption algorithm to be used and the list of data to be encrypted are:

[0066] Construct vehicle maintenance analysis model according to demand objectives;

[0067] Generate a list of data to be encrypted according to the vehicle maintenance model;

[0068] The name of the encryption algorithm to be used is determined based on the list of data to be encrypted.

[0069] In one embodiment, the vehicle maintenance analysis model is expressed as:

[0070] LSC=LSC cm +LSC pm =N cm (H cm *C labor +C part )+N pm1 (H pm1 *C labor +

[0071] η*C part 0+N pm2 (H pm2 *C labor +C part );

[0072] In the formula, LSC cm To repair the maintenance sub-model; LSC pm N is the preventive maintenance submodel; cm H is the number of repair and maintenance times; cm Repair and maintenance hours; C labor C is the unit labor time fee; part is the component price; N pm1 The number of maintenance times for preventive disassembly and overhaul; H pm1 is the maintenance man-hours for preventive disassembly and overhaul; η is the proportion of material costs for preventive disassembly and overhaul; N pm2 Number of maintenance to prevent replacement; H pm2 Maintenance hours for preventive replacement.

[0073] In one embodiment, the list of data to be encrypted includes unit labor time costs, prices of spare parts and consumables required for repair and maintenance, and prices of spare parts and consumables required for preventive maintenance.

[0074] Furthermore, it may also include the number of repair and maintenance times of each component, the number of repair and maintenance man-hours, the number of spare parts and consumables required for the repair and maintenance, the number of preventive maintenance times, the number of preventive maintenance man-hours and the number of spare parts and consumables required for preventive maintenance, etc.

[0075] In one embodiment, a specific example of application is used for illustration. The vehicle maintenance analysis model includes at least a repair and maintenance sub-model and a preventive maintenance sub-model. The repair and maintenance sub-model includes at least a repair and maintenance labor cost and a repair and maintenance spare parts and consumables cost. The preventive maintenance sub-model includes at least a preventive maintenance labor cost model and a preventive maintenance spare parts and consumables cost, that is:

[0076] Vehicle maintenance analysis model = repair maintenance sub-model + preventive maintenance sub-model =

[0077] Repair and maintenance labor cost + repair and maintenance spare parts and consumables cost + preventive maintenance labor cost +

[0078] Preventive maintenance spare parts and consumables costs;

[0079] The required input items generally include at least the number of repair and maintenance of the relevant parts, the repair and maintenance man-hours, the unit labor-hour cost, the number of spare parts and consumables involved in the repair and maintenance and their prices, the number of preventive maintenance, the preventive maintenance man-hours, the number of spare parts and consumables involved in the preventive maintenance and their prices. For example: the repair and maintenance spare parts and consumables cost of any part can be calculated by the following formula: Where N cm The number of repairs of the component, N i The number of the i-th spare parts and consumables required to repair the component, C i is the price of the i-th spare part.

[0080] Furthermore, it is necessary to analyze the full life cycle maintenance costs of a certain component installed on rail vehicles. The known conditions are as follows: the component is a non-repairable product with a failure rate of 0.1FPMK. It needs to be replaced as a whole in case of failure. The replacement operation requires 2 maintenance personnel and takes 1 hour. The full life cycle is 30 years, with an annual running mileage of 600,000 kilometers. It needs to be disassembled and repaired once every 3 years. Disassembly and repair requires 3 personnel and takes 3 hours. The material cost of disassembly and repair is 20% of the component price. It needs to be replaced every 12 years. Replacement requires 2 maintenance personnel and takes 1 hour. The cost of consumables is ignored.

[0081] It can be seen that the number of repairs and maintenance N cm =0.1*30*60 / 100=1.8 times; repair and maintenance hours H cm =2*1=2 man-hours; number of preventive disassembly and maintenance Maintenance hours for preventive disassembly and overhaul H pm1 =3*3=9 man-hours; number of preventive replacements times; maintenance hours for preventive replacement H pm2 =2*1=2 person hours.

[0082] Then the required analysis model can be obtained as follows:

[0083] LSC=LSC cm +LSC pm =N cm (H cm *C labor +C part )+N pm1 (H pm1 *C labor +

[0084] 20%*C part )+N pm2 (H pm2 *Clabor +C part );

[0085] In addition to the number of times and working hours calculated above, the model also requires the unit labor cost C provided by the financial platform. labor and component price C part .

[0086] In one embodiment, an appropriate homomorphic encryption algorithm is selected according to the composition of the analysis model and the available computing resources. The data to be encrypted includes at least price data; when only addition is involved between the encrypted data, an additive semi-homomorphic algorithm can be selected, such as the Paillier algorithm; when only multiplication is involved, a multiplication semi-homomorphic algorithm can be selected, such as the RSA algorithm and the ElGamal algorithm; when both addition and multiplication are involved, a quasi-homomorphic encryption algorithm or a fully homomorphic encryption algorithm can be selected, such as the BGN scheme, the Gentry scheme, the BGV / BFV scheme, the GSW scheme, the CKKS scheme, etc.

[0087] Substituting the known data into the analysis model, we can obtain:

[0088] LSC=LSC cm +LSC pm =1.8(2*C labor +C part )+7(9*C labor +20%*C part )+2(2*C labor +C part );

[0089] After sorting, we can get:

[0090] LSC=70.6*C labor +5.2*C part ;

[0091] LSC cm =3.6*C labor +1.8*C part ;

[0092] LSC pm =67*C labor +3.4*C part ;

[0093] According to the characteristics of the model, the Paillier algorithm is selected in this example.

[0094] In one embodiment, when using the established model to conduct economic analysis, at least two system platforms are involved, one is the system platform for economic analysis (hereinafter referred to as the analysis platform, i.e., the second platform), and the other is the system platform for providing price data (hereinafter referred to as the financial platform, i.e., the first platform). The financial platform is mainly responsible for key generation, price data encryption, and calculation result decryption in the homomorphic encryption algorithm; the analysis platform is mainly responsible for related data encryption and homomorphic encryption calculation.

[0095] In one embodiment, the analysis platform first sends the name of the homomorphic encryption algorithm to be used (the name of the encryption algorithm to be used) and the detailed list of data to be encrypted (i.e., the list of data to be encrypted) to the financial platform based on the model calculation requirements.

[0096] Further, the analysis platform will provide the required price details list {C labor , C part} and the algorithm name Paillier are sent to the financial platform.

[0097] In one embodiment, the financial platform applies a specified encryption algorithm to generate a public key and a private key, extracts the corresponding price data according to the detailed list and encrypts it using the public key, and returns the encrypted price data and the corresponding public key.

[0098] Furthermore, after the financial platform receives the request from the analysis platform, it first generates the public key and private key required for calculation according to the encryption algorithm specified by the analysis platform; then it retrieves and extracts the corresponding price data from the financial platform according to the data details table and encrypts the data using the public key; the encrypted data and public key are returned to the analysis platform; in order to meet the requirements of the encryption algorithm under normal circumstances, the price data should be extracted and encrypted in units of cents (that is, the value should be guaranteed to be a positive integer).

[0099] Furthermore, after receiving the request, the financial platform first generates the public key and private key corresponding to the Paillier algorithm based on the analysis platform requirements.

[0100] The following uses the Python environment as an example to illustrate the implementation process. The implementation process in other environments is similar:

[0101] fromphe importpaillier;

[0102] public_key,private_key=paillier.generate_paillier_keypair();

[0103] Next, retrieve and extract the corresponding price data (unit labor cost C according to the data detail table) labor is 5000 points, component price C partis 581538 points), encrypt the data using the public key:

[0104] secret_number_list=[5000,581538];

[0105] encrypted_number_list=[public_key.encrypt(x)forx in secret_number_list]

[0106] Then, the financial platform returns the public key (public_key) and the encrypted detailed data (encrypted_number_list), namely the first encrypted data, to the analysis platform.

[0107] In one embodiment, the steps of obtaining the encryption calculation result are:

[0108] receiving first encrypted data and a public key;

[0109] Using the public key to encrypt the data to be calculated, to obtain second encrypted data;

[0110] Substitute the first encrypted data and the second encrypted data into the vehicle maintenance analysis model to obtain an encrypted calculation result.

[0111] In one embodiment, the encrypted price data is substituted into the analysis model calculation, and other data required for the calculation is encrypted by the public key when necessary and substituted into the analysis model calculation, and the calculation result data set is sent to the source system. When the expansion coefficient method is used to ensure accuracy or eliminate floating point operations, the corresponding expansion coefficient needs to be transmitted.

[0112] Furthermore, after receiving the returned encrypted data and public key, the analysis platform uses the public key to encrypt other data that needs to be encrypted to participate in the calculation as needed, and then substitutes the encrypted data into the analysis model for calculation to obtain the encrypted calculation results.

[0113] The analysis platform sends the calculation results that need to be decrypted to the financial platform. The calculation results generally include at least the total maintenance guarantee cost, the total repair and maintenance cost, the total preventive maintenance cost, etc.

[0114] Furthermore, the analysis platform receives the encrypted data encrypted_number_list and, according to the detailed list: encrypted_number_list[0] is the encrypted unit labor cost C labor ,encrypted_number_list[1] is the encrypted component price component price C part ,

[0115] Substitute the encrypted data into the model to calculate the desired result:

[0116] encrypt_res_lsc=706*encrypted_number_list[0]+52*encrypted_number_list[1];

[0117] encrypt_res_lsc_cm=36*encrypted_number_list[0]+18*encrypted_number_list[1];

[0118] encrypt_res_lsc_pm=670*encrypted_number_list[0]+34*encrypted_number_list[1];

[0119] To ensure the accuracy of the algorithm, the input model coefficients were expanded 10 times during calculation.

[0120] In one embodiment, after the calculation is completed, the analysis platform sends the encrypted data encrypt_res_lsc, encrypt_res_lsc_cm, encrypt_res_lsc_pm of the calculation results and the expansion factor: 10 to the financial platform.

[0121] In one embodiment, the transformation process is a desensitization process or a conversion calculation.

[0122] Furthermore, after receiving the calculation results sent by the analysis platform, the financial platform uses the private key to decrypt the result data and obtain the real calculation results. Then, according to the enterprise's data management requirements, the calculation results are desensitized or converted in the agreed manner. Desensitization methods usually include replacement or numerical variation, etc. The conversion calculation is such as the total maintenance guarantee cost, total repair and maintenance cost, and total preventive maintenance cost obtained through actual calculation, and the repair and maintenance cost ratio and preventive maintenance cost ratio are calculated respectively. Finally, the desensitized data or the converted percentage data are returned to the analysis platform.

[0123] Furthermore, the financial platform uses the private key to decrypt the calculation results sent by the analysis platform:

[0124] calc_res_lsc=private_key.decrypt(encrypt_res_lsc) / 10;

[0125] calc_res_lsc_cm=private_key.decrypt(encrypt_res_lsc) / 10;

[0126] calc_res_lsc_pm=private_key.decrypt(encrypt_res_lsc) / 10;

[0127] After decryption, the calculation result is obtained in plain text:

[0128] calc_res_lsc=3376997.6;

[0129] calc_res_lsc_cm=1064768.4;

[0130] calc_res_lsc_pm=2312229.2;

[0131] Assume that the agreed requirement is that the total cost result is in units of 10,000 yuan, and is returned after random value mutation within the range of ±10%. The cost items that make up the total cost are returned as percentages, and the actual value is not returned:

[0132] return_res_lsc=calc_res_lsc / 1000000*(1+random.uniform(-.1,.1));

[0133] return_res_lsc_cm=calc_res_lsc_cm / calc_res_lsc;

[0134] return_res_lsc_pm=calc_res_lsc_pm / calc_res_lsc;

[0135] After calculation, the calculation result returned by the financial platform to the analysis platform is:

[0136] return_res_lsc=3.2322425905252627;

[0137] return_res_lsc_cm=0.3153003129170124;

[0138] return_res_lsc_pm=0.6846996870829876;

[0139] In one embodiment, after receiving the analysis results returned by the financial platform, the analysis platform further completes the required economic analysis work, such as classifying and summarizing the analysis results, sorting them, and forming a list of key economic factors.

[0140] Furthermore, after the analysis platform receives the results returned by the financial platform, it can be learned that the maintenance cost of the component throughout its life cycle is approximately 30,000 yuan, of which preventive maintenance costs account for approximately 68.47% and repair maintenance costs account for approximately 31.53%.

[0141] Based on the analysis results, the designers can preliminarily determine that the main direction of the component strategy optimization is to reduce the cost of preventive maintenance. Specifically, it includes extending the maintenance interval, shortening the maintenance time, and reducing the cost of disassembly and maintenance.

[0142] Another aspect of the present invention discloses a rail transit vehicle maintenance strategy optimization system based on homomorphic encryption, which applies the above method and includes:

[0143] A data receiving module, used for receiving the name of the encryption algorithm to be used and the list of data to be encrypted;

[0144] A data extraction module, used to call the encryption algorithm according to the name of the encryption algorithm to be used, and extract the data to be encrypted according to the data list to be encrypted;

[0145] A key generation module, used to generate public keys and private keys according to encryption algorithms;

[0146] An encryption processing module, used to encrypt the data to be encrypted using a public key to generate first encrypted data;

[0147] A first data exchange module, used to send the first encrypted data and the public key to the second platform, and receive the encryption calculation result sent by the second platform;

[0148] The decryption processing module is used to receive the encrypted calculation result and decrypt the encrypted calculation result using the private key to obtain the real calculation result;

[0149] The data transformation module transforms the real calculation results to generate transformation data;

[0150] A second data exchange module, used for sending the transformed data to the second platform;

[0151] The strategy optimization module is used to optimize the vehicle maintenance strategy according to the transformed data.

[0152] In one embodiment, it further includes:

[0153] A model building module is used to build a vehicle maintenance analysis model according to demand objectives;

[0154] A data screening module, used to generate a list of data to be encrypted according to a vehicle maintenance model;

[0155] The algorithm selection module is used to determine the name of the encryption algorithm to be used according to the list of data to be encrypted.

[0156] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0157] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A rail transit vehicle maintenance strategy optimization method based on homomorphic encryption, characterized in that: The specific steps are: Encryption process: The first platform receives the name of the encryption algorithm to be used and the list of data to be encrypted; Calling an encryption algorithm according to the name of the encryption algorithm to be used, and extracting the data to be encrypted according to the list of data to be encrypted; Generate a public key and a private key according to the encryption algorithm; Encrypting the data to be encrypted using the public key to generate first encrypted data; Sending the first encrypted data and the public key to the second platform, and receiving the encryption calculation result sent by the second platform; Decryption process: The first platform receives the encrypted calculation result, and decrypts the encrypted calculation result using the private key to obtain a real calculation result; Performing transformation processing on the real calculation result to generate transformation data; The transformed data is transmitted to the second platform, and the vehicle maintenance strategy is optimized according to the transformed data.

2. According to claim 1, a rail transit vehicle maintenance strategy optimization method based on homomorphic encryption is characterized in that: The steps for obtaining the name of the encryption algorithm to be used and the list of data to be encrypted are: Construct vehicle maintenance analysis model according to demand objectives; generating the data list to be encrypted according to the vehicle maintenance model; The name of the encryption algorithm to be used is determined according to the list of data to be encrypted.

3. According to claim 2, a rail transit vehicle maintenance strategy optimization method based on homomorphic encryption is characterized in that: The expression of the vehicle maintenance analysis model is: LSC=LSC cm +LSC pm =N cm ( H cm *C labor +C part ) +N pm1 ( H pm1 *C labor + η*C part ) +N pm2 ( H pm2 *C labor +C part ) ; In the formula, LSC cm To repair the maintenance sub-model; LSC pm N is the preventive maintenance submodel; cm H is the number of repair and maintenance times; cm Repair and maintenance hours; C labor C is the unit labor time fee; part is the component price; N pm1 The number of maintenance times for preventive disassembly and overhaul; H pm1 is the maintenance man-hours for preventive disassembly and overhaul; η is the proportion of material costs for preventive disassembly and overhaul; N pm2 Number of maintenance to prevent replacement; H pm2 Maintenance hours for preventive replacement.

4. According to claim 2, a rail transit vehicle maintenance strategy optimization method based on homomorphic encryption is characterized in that: The data list to be encrypted includes unit labor costs, prices of spare parts and consumables required for repair and maintenance, and prices of spare parts and consumables required for preventive maintenance.

5. According to the method for optimizing rail transit vehicle maintenance strategy based on homomorphic encryption in claim 1, it is characterized in that: The steps for obtaining the encryption calculation result are: receiving the first encrypted data and the public key; Using the public key to encrypt the data to be calculated, to obtain second encrypted data; Substituting the first encrypted data and the second encrypted data into the vehicle maintenance analysis model to obtain the encrypted calculation result.

6. The method for optimizing rail transit vehicle maintenance strategy based on homomorphic encryption according to claim 1 is characterized in that: The transformation process is a desensitization process or a conversion calculation.

7. A rail transit vehicle maintenance strategy optimization system based on homomorphic encryption, characterized in that: include: A data receiving module, used for receiving the name of the encryption algorithm to be used and the list of data to be encrypted; A data extraction module, used to call the encryption algorithm according to the name of the encryption algorithm to be used, and extract the data to be encrypted according to the list of data to be encrypted; A key generation module, used to generate a public key and a private key according to the encryption algorithm; An encryption processing module, used to encrypt the data to be encrypted using the public key to generate first encrypted data; A first data exchange module, used to send the first encrypted data and the public key to the second platform, and receive the encryption calculation result sent by the second platform; A decryption processing module, used to receive the encrypted calculation result, and use the private key to decrypt the encrypted calculation result to obtain a real calculation result; A data transformation module performs transformation processing on the real calculation result to generate transformation data; A second data exchange module, used for sending the transformed data to the second platform; A strategy optimization module is used to optimize the vehicle maintenance strategy according to the transformed data.

8. A rail transit vehicle maintenance strategy optimization system based on homomorphic encryption according to claim 7, characterized in that: Also includes: A model building module is used to build a vehicle maintenance analysis model according to demand objectives; A data screening module, used for generating the data list to be encrypted according to the vehicle maintenance model; The algorithm selection module is used to determine the name of the encryption algorithm to be used according to the list of data to be encrypted.

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