Design of financial management database for automobile enterprises based on image encryption algorithm

doi:10.21203/rs.3.rs-2749659/v1

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Design of financial management database for automobile enterprises based on image encryption algorithm

https://doi.org/10.21203/rs.3.rs-2749659/v1

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The automobile industry has a history of more than 100 years in foreign countries, so it is the continuous progress of professional automobile enterprises that has promoted the continuous development of the automobile industry. Financial management and database system provide many automobile companies with the best financial management solutions in the industry. As the core of financial management, it is highly integrated with the fixed assets module, which makes the financial management in the information management system of automobile enterprises closely connected with the daily management of automobile enterprises. At present, the original data management of each unit in the financial management system of automobile enterprises is still not subject to regulatory control, and the financial responsibility and financial data are often inaccurate. The current financial system is not scientific in product pricing, and it is difficult to provide detailed and accurate cost analysis and difference analysis results. Finally, for automobile enterprises, a unified and integrated financial management database system should be used to better manage the financial and operating conditions of automobile companies. After outlining the general procedures of the encryption algorithm, this document introduces the security characteristics and sensitivity analysis of the image encryption algorithm key. The security of the image encryption algorithm is strengthened, and the encrypted image is checked separately. Based on this content, this paper analyzes the financial management system of automobile enterprises in general, and explains the process of fixed assets storage and special storage in the software. Then, by optimizing the overall structure design of financial management, the system design of financial management database is proposed. After understanding the shortcomings of current financial software in meeting user needs, the design objectives and tasks of financial management database are provided, and the system design of automobile financial management database is summarized, and the outlook after the system design is put forward.

image encryption algorithm

Automobile enterprises

Financial management

database

Since its birth in 1886, the automobile as a means of transportation has gradually been presented by human technology, so the industry has also become an indispensable human technology in the world. Over the past few decades, the automobile has gradually become the main pillar of human development, and has a profound impact on the development of the world economy and social progress [1]. Behind this huge contribution, the development of automobile enterprises is one of the main driving factors. With the continuous progress of information technology, more and more companies need to improve computer technology, so as to change their backward problems in dealing with accounting information. Therefore, on the one hand, different companies have different requirements for financial software, and the same company's requirements for financial software operation will change at different times; On the other hand, financial accountants have increasingly high requirements for computer software [2]. They hope that the system can work efficiently and meet their personal interface requirements. Financial software requires to provide services organically according to the needs of users, better solve various problems faced by users, better protect the interests of users, and greatly improve the work efficiency of accountants. After nearly a hundred years of practice, developed countries have accumulated rich experience in automobile management services, thus establishing a consumer market covering various services [3]. In China, although the automobile consumption market has developed rapidly, the financial management service of automobile is still in the initial stage, the price of automobile market fluctuates greatly, the operating cost of automobile companies is high, and the social credit awareness is lacking. It is very difficult to carry out auto financial management services in China, and it will take time to form a better auto financial management system [4]. In this process, we can learn from the experience of foreign mature auto financing service industry. The real situation of China cannot be ignored. On the one hand, the opening of finance is gradually in line with international standards; On the other hand, it is to arrange wealth management products and services according to China's market conditions and national conditions. To form a car financing service system with Chinese characteristics. With the rapid development of information transmission technology, digital image, as an intuitive and efficient transmission medium, is often used as a tool for transmitting information [5]. If the image information is stolen by criminals, it may cause unnecessary losses to individuals, automobile companies and even the country. The traditional encryption algorithms such as DES, RSA, IDEA are mainly text encryption, and the effect of image encryption is not appropriate. Therefore, it is urgent to design an efficient and fast image encryption algorithm for image encryption. Chaos is widely used in image encryption algorithms because of its inherent randomness, unpredictability and high sensitivity to initial values [6]. Chaotic maps include low-dimensional maps and high-dimensional maps. These low-dimensional maps are simple and efficient, but lack security. There are many drafting standards with high security, but low efficiency and waste of resources. Therefore, two-dimensional mapping is used to improve the security of chaotic mapping, while also ensuring the computational efficiency. For color image encryption algorithms, the complexity of chaotic mapping alone is not enough to ensure its security [7]. Chaos and diffusion are important components of the algorithm. Bit method increases the computation of the algorithm, and the encryption efficiency is low. All three channels use the same encryption method, so attackers can obtain complete image information by decomposing the contents of a single channel, and the security of the encryption algorithm is low [8]. Chaotic sequence sorting is used to destroy plain images and improve the overall encryption effect of color images, but the diffusion part is simple. In view of the shortcomings of the research, an image encryption algorithm is proposed to optimize the financial management system of automobile enterprises, and the financial management database system is designed considering the practical drawbacks [9].

The literature points out that auto financing companies are a type of financial companies [10]. Since then, financial companies have gradually become a new type of non-bank financial institutions to meet customers' credit needs. The literature points out that ERP was launched decades earlier than China, and was initially mainly used for the construction of large enterprises, inventory management and control, and was not combined with financial management [11]. After decades of development, the ERP software field led by the German SAP system has integrated almost all enterprise information, including financial accounting, material management, inventory management, production planning, marketing, equipment, labor, quality control, etc. SAP system has been applied to different degrees in manufacturing, retail, petrochemical, power, banking and other industries. Large enterprises in developed countries abroad have widely adopted SAP system as a platform for company production, operation management and decision support. Management information technology has now been widely implemented. Manufacturing is one of the more mature industries that use the financial management subsystem of SAP system. The literature focuses on the core of the enterprise - financial management system, and implements sub-modules such as account calculation, collection accounting, payment accounting, fixed assets, capital, and financial risk management [12]. In management accounting, cost objects and cost flows are enabled; The comparative competency analysis sub-module enables the mature application of cost and difference analysis, difference decomposition, retrospective analysis and adjustment of each difference and the profitability of each department in the enterprise. From the storage of raw materials to the production of intermediate and final products, and finally to the sales chain of delivering products to consumers. The literature points out that with the support of SAP system, foreign large enterprises can effectively manage and monitor, balance various resources of enterprises, strengthen the financial management of enterprises, improve the operation level of funds, and establish efficient supply chain [13]. Improve production efficiency, reduce production costs, and realize business intelligence. To sum up, the implementation and application of ERP in foreign large enterprises started earlier than China, and the application of modules is more extensive. The literature points out that after decades of development and business application, the coverage and operation of products are increasing [14]. In the current information society, the use of cyberspace technology is increasing, and the transmission of digital multimedia information, especially image information, is also increasing. Because the image contains part of the confidentiality and privacy of enterprises and individuals, special attention should be paid to the security of image information transmitted in cyberspace. In order to ensure the security of image information transmitted in cyberspace, appropriate encryption methods should be adopted to encrypt image information to avoid information leakage during image transmission. Because image information is characterized by high redundancy and information, it is necessary to select more effective encryption methods for encryption processing. A mapping content is designed in the literature, which makes it more suitable for designing the fusion of secure cryptographic systems.

3.1 Image encryption algorithm

In order to reflect whether the histogram of the encrypted image is more scientifically and objectively uniformly distributed, we use formula (1) to give the entropy of the encrypted image information:

$$\text{H}\left(\text{p}\right)=\sum _{\text{i}=0}^{\text{L}-1}\text{p}\left(\text{p}\text{i}\right){\text{l}\text{o}\text{g}}_{2}\frac{1}{\text{p}\left(\text{p}\text{i}\right)}$$

In this paper, the image variable function is introduced to measure the difference between the encrypted image and the actual image, that is, its chaotic quantity. The entropy of source information (i.e., plain text image) is H (p), and the entropy of destination information (i.e., encrypted image) is H (C), and their conditional entropy H (c/p) is generated. When obtaining ciphertext in Figure C, it can be assumed that the average amount of mutual information about plain text P will be obtained. If I (P; C) = 0, in this case, information about plain text images cannot be obtained from ciphertext images.

$$\text{H}(\text{c}/\text{p})=-\sum _{\text{j}=1}^{\text{n}}\sum _{\text{e}=1}^{\text{n}}\text{p}\left({\text{p}}_{\text{j}}{\text{c}}_{\text{e}}\right){\text{l}\text{o}\text{g}}_{2}\text{p}({\text{c}}_{\text{e}}/{\text{p}}_{\text{j}})$$

As an example of testing the performance of its algorithm specifically for the above indicators, we will use the logic diagram encryption algorithm in the chaotic image encryption algorithm. The Henon map is a classic two-dimensional map, and its mathematical expression is shown in (3):

$$\left\{\begin{array}{c}{\text{x}}_{\text{i}+1}=1-a{\text{x}}_{\text{i}}^{2}+{\text{y}}_{\text{i}}\\ {\text{y}}_{\text{i}+1}=a{\text{x}}_{\text{i}}\end{array}\right.$$

Although there is some chaos under the parameters suitable for the above mapping, the encryption effect is not appropriate due to its small chaotic interval and simple chaotic behavior. Therefore, a dynamic 2DHCLM chaotic map is designed. By introducing the cosine mapping formula and extending the chaotic interval to about 0 and embedding the dynamically adjusted parameter W, the chaotic behavior becomes more complex:

$$\left\{\begin{array}{c}{\text{x}}_{\text{i}+1}=(1-a{\text{x}}_{\text{i}}^{2}+{\text{y}}_{\text{i}})cos\left(w\pi {\text{x}}_{\text{i}}\right)\\ {\text{y}}_{\text{i}+1}=b{\text{x}}_{\text{i}}cos\left(w\pi {\text{y}}_{\text{i}}\right)\\ w=abs\left(u{\text{x}}_{\text{i}}\right(1-{\text{x}}_{\text{i}}\left)\right)\times 10\end{array}\right.$$

In order to check the average correlation information value of the chaotic image encryption algorithm, scan the plain text image and the corresponding ciphertext image to obtain the probability distribution of pixels, and then calculate the average correlation information I (p; c) according to the following formula (5):

$$\text{I}(\text{p};\text{c})=\text{H}\left(\text{c}\right)-\text{H}(\text{c}/\text{p})=0.003916$$

According to the above equation, input the randomly selected initial value x ∈ [0,1] and parameter u = 3.99, and change it to formula iteration (v + M × N) Times, discard the first v = 1000 digits, and then use the above formula to process the chaotic sequence to obtain the pseudo-random sequence X:

$$\text{X}=\text{m}\text{o}\text{d}\left(\text{x}\text{m}\right(\text{v}+1:\text{v}+\text{M}\times \text{N})\times {10}^{4},6)$$

A0, B0, A0, B0, B0 and B0 are used for row scrambling and column scrambling of digital image matrix respectively.

$$\left\{\begin{array}{c}X0=x(v+1:v+N\times 3)\\ Y0=y(v+1:v+M)\end{array}\right.$$

Interpria information is an indicator of image information analysis, because information is a high-quality image with high pixel quality and good image coding. This algorithm completely hides the original image content through two rounds of scrambling and two rounds of diffusion, thus increasing the information entropy of the ciphertext image. The calculation method of information entropy is as follows:

$$\text{H}\left(\text{a}\right)=-\sum _{\text{i}=0}^{\text{N}}\text{P}\left(\text{a}\text{i}\right){\text{l}\text{o}\text{g}}_{2}\text{P}\left(\text{a}\text{i}\right)$$

The specific operation is shown in Fig. 1. According to the corresponding numbers in matrix L, matrices Ir, Ig and Ib are scrambled across the plane, and the three levels are combined into matrix P (M × N × 3), as shown in Fig. 1.

3.2 Key generation

The chaotic image in the encryption process can be expressed by formula (9):

$$\text{H}={\text{B}}^{\text{i}}\left({\text{F}}^{\text{j}}\right(\text{Q},{\text{K}}_{\text{F}}),{\text{K}}_{\text{B}})$$

The realization accuracy of the chaotic system is limited. The period of the chaotic sequence obtained by measuring the number of chaotic maps of various chaotic parameters, that is, the period of the chaotic parameter and the period of state a (i), are equivalent to the period of the chaotic sequence generated by the chaotic system.

Here, the logistics chaotic map and the coase map of PLCM are combined to form a variable parameter multistage chaotic system. The chaotic map parameters can be randomly arranged, and the system can be used to create a modifiable sequence. Among them, chaotic map is a common chaotic map, which is expressed as (10) in chaotic system:

$${\text{a}}_{\text{m}+1}=\text{E}({\text{a}}_{\text{m}},{\eta })={\eta }{\text{a}}_{\text{m}}-{{\eta }\text{a}}_{\text{m}}^{2}$$

When the number of repetition is greater than T1, the chaotic parameter q can be expressed as follows:

$$\text{q}=\frac{{\text{E}}_{3{\eta }}\left(\text{a}\right(\text{t}-1),{\eta })}{3}$$

Use any complex chaotic sequence created by the variable parameter multistage chaotic system in the previous section to construct the invertible integer matrix. The value of the chaotic sequence an (t) i is not less than 0. By using o (an (t) i) ij to construct a matrix of order n as an element, it can be expressed as follows (12):

$$\text{O}\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)=\left[\begin{array}{cc}\text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{11}& \begin{array}{ccc}\text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{12}& \cdots & \text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{1\text{n}}\end{array}\\ \begin{array}{c}\text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{21}\\ \cdots \\ \text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{\text{m}1}\end{array}& \begin{array}{ccc}\begin{array}{c}\text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{22}\\ \cdots \\ \text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{\text{m}2}\end{array}& \begin{array}{c}\cdots \\ \cdots \\ \cdots \end{array}& \begin{array}{c}\text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{2\text{n}}\\ \cdots \\ \text{o}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{\text{m}\text{n}}\end{array}\end{array}\end{array}\right]$$

The expression of w (an (t) i) ij element of matrix is shown in (13):

$$\text{w}{\left({\text{a}}_{\text{n}}{\left(\text{t}\right)}_{\text{i}}\right)}_{\text{i}\text{j}}={(-1)}^{\text{i}+\text{j}}$$

In the process of modeling, according to the image before and after modeling, H and G images are used respectively. It is necessary to extend any pixel information of the plaintext to the whole image of the ciphertext. The forward algorithm is shown in the following formula (14):

$${\text{G}}_{\text{i}}=({\text{G}}_{\text{i}-1}+{\text{s}}_{\text{i}}+{\text{H}}_{\text{i}})\text{m}\text{o}\text{d}256$$

In this paper, two-dimensional generalized Arnold map is used, and the formula is as follows (15):

$$\left(\begin{array}{c}{\text{x}}^{{\prime }}\\ {\text{y}}^{{\prime }}\end{array}\right)={\left(\begin{array}{cc}1& \text{a}\\ \text{b}& \text{a}\text{b}+1\end{array}\right)}^{\text{n}}\left(\begin{array}{c}\text{x}\\ \text{y}\end{array}\right)\text{m}\text{o}\text{d}\text{N}$$

CNN is a neural network system constructed by interconnection of local cells. The dynamic equation of 3DCNN system is as follows:

$$\frac{{\text{d}\text{x}}_{\text{j}}}{\text{d}\text{t}}=-{\text{x}}_{\text{j}}+{\text{a}}_{\text{j}}\text{f}\left({\text{x}}_{\text{j}}\right)+\sum _{\text{k}=1}^{3}{\text{A}}_{\text{j}\text{k}}\text{f}\left({\text{x}}_{\text{k}}\right)+\sum _{\text{k}=1}^{3}{\text{S}}_{\text{j}\text{k}}{\text{x}}_{\text{k}}+{\text{I}}_{\text{j}}$$

The plain text image is developed as A one-dimensional vector using PM×N rows or columns and recorded as A. Step 1 is used to create 3d chaos series and establish the initial CNN chaos system length. x3(i), this function includes a top-down function, because a series of chaotic states have broad value, not suitable for data collection work, so the following preprocessing needs to be optimized:

$${\text{x}}_{1}\left(\text{i}\right)={10}^{14}{\text{x}}_{1}\left(\text{i}\right)-\text{f}\text{l}\text{o}\text{o}\text{r}\left({10}^{14}{\text{x}}_{1}\right(\text{i}\left)\right)$$

As shown in Table 1, the average NPCR and UGI calculated in the algorithm in this document are very close to the ideal value. Compared with other algorithms, the algorithm proposed in this paper is more sensitive to small changes in plain text, so the algorithm is more effective against differential attacks.

Table 1

Sensitivity test results
Algorithm		Text	Existing algorithms	Algorithm in this paper
Average value	NPCR	0.9846	0.9965	0.9965
Average value	UACI	0.3254	0.3346	0.3365
Ideal value	NPCR	0.9874	0.9874	0.9874
Ideal value	UACI	0.3387	0.3387	0.3387

The correlation coefficient of adjacent pixels is calculated as shown in formula (18).

$$\text{E}\left(\text{x}\right)=\frac{1}{\text{N}}\sum _{\text{i}=1}^{\text{N}}{\text{x}}_{\text{i}}$$

The parameters of CNN are as follows, but the chaos generated by CNN system is shown in formula (19) (20).

$$\text{A}=\left(\begin{array}{cc}3.88& \begin{array}{cc}0& 0\end{array}\\ \begin{array}{c}0\\ 0\end{array}& \begin{array}{cc}\begin{array}{c}0\\ 0\end{array}& \begin{array}{c}0\\ 0\end{array}\end{array}\end{array}\right)$$

As shown in Table 2, the calculated NPCR and UQI values can be seen to be close to the ideal values. Therefore, the main sensitivity of this algorithm is strong.

Table 2

Key sensitivity test results
Index		NPCR	UACI	NPCR	UACI	NPCR	UACI
Encryption	Experimental value	99.68	33.48	99.84	33.65	99.85	33.55
Encryption	Ideal value	99.85	33.48	99.84	33.64	99.86	33.24

4.1 Optimization of financial management system of automobile enterprises

In the fixed asset purchase business, when filling in the asset purchase application according to the actual situation of the automobile enterprise, the cost center has not yet been finalized, and an asset may have a value to be added later, or it cannot be temporarily posted because the invoice has not been reached. The problem is that, first of all, if the asset value is added in the next month, the new added value can only be calculated in the next month, which cannot accurately reflect the consumption of actual expenditure, and ultimately affects the cost accounting of the current month. Secondly, if the cost center is not determined when the master data is created, it can be clarified later. Then some costs may have been accumulated in the original cost center, thus increasing the actual cost of the cost center. This is one of the reasons for poor asset master data management and inaccurate finished product cost of automobile enterprises. For this business purpose, the optimization recommended in this section is to set the asset card in the construction schedule when the financial personnel create the asset card. Before converting the construction project into fixed assets, determine the final cost center and correctly maintain its transferred fixed asset card. The recommended process is shown in Fig. 3.

In supplier master data maintenance, company code level data is associated with financial related information (such as reconciliation accounts, payment terms and payment methods). Generally, there are two types of accounts payable vouchers. One is through the purchase process, that is, from the purchase order, the receipt to the warehouse, and the posted prefabricated invoice; Secondly, accounts payable bills are directly generated by the financial department without going through the purchase department.

After investigation, in the warehousing business of auto enterprises, there are specific business situations that help customers purchase assets. The purchase process is similar to the normal asset purchase process. However, since such assets are not handled by auto enterprises as their own assets, they should not be recorded into the asset account of auto enterprises.

In terms of data uploading, the existing LSMW tool is based on SAP standard batch input technology. After testing and analysis, the following problems are found. Thirdly, external numbers cannot be used to generate financial vouchers, so it is difficult to track each voucher number generated after uploading through LSMW. Because the data cannot be found, problems will occur. This requires reversing the voucher, which is also a time-consuming work. Through the analysis of SAP's numerous data import technologies, we try to find the appropriate BAPI to write ABAP custom programs, and design data import programs to improve performance.

4.2 Design of financial management database for automobile enterprises

The development of computer accounting information system includes two basic and most important steps: system analysis and system design. The main task of system analysis is to investigate, study, understand and analyze the situation, and propose a reasonable model of accounting information computerization, which solves the problem of how to do the system; According to the logic mode proposed in the system analysis stage, the main task of the system design is to ensure that the advantages and disadvantages of various technical methods used in the system are balanced from a comprehensive perspective. At the final stage of micro-design, programmers begin to program and finally describe the entire computerized accounting information system.

The database technology accounting information system provides researchers with powerful tools to scientifically organize the data of the accounting information system, write programs, and finally realize the data processing function. In this sense, database technology is designed for accounting information systems. In the computerized accounting information system, it is pointed out that the concept of database and command file is one of the concepts commonly used by developers in the system analysis and system design stage before the formal scheme preparation. Of course, in order to develop accounting information system and database technology, we need at least some system analysis and system design technology, so as to better understand the content of the whole system from the overall perspective.

Accounting data is the main objective of making accounting information system. When raw data enters the system, no matter which link or step, it may be based on the needs of specific information users. Through program design, various accounting information can be output, which can be various account information generated by classification records, or account system information processed according to double-entry bookkeeping method: or accounting statement information. However, in any case, the information provided in the report should be the main objective of the system. Therefore, we only consider the information provided in the data flow diagram of the tracking system, and delete some outputs from the intermediate information, although sometimes very useful. However, the final result of the system analysis should take the database flow chart in Fig. 5 as the main reference. Figure 5 shows the flow chart of top-level data. The word 0 at the top of the circle indicates the 0 layer, that is, the upper layer.

The second layer of data flow diagram can be made according to the first layer of data flow diagram; However, in order to clarify the flow direction of data flow in the module, we have listed the second layer of data flow diagram one by one in the detailed design of each module. Don't mistakenly think that the flow chart of basic data can be output only when the detailed design is required. However, the data flow is the product of the system analysis stage. In order to enable the majority of users to accept the output information, it is necessary to recall all operation codes (including account codes) back to Chinese information and establish account dictionaries according to the standard inspection methods of English and Chinese dictionaries. Because the topic dictionary itself is a database file, it is called the topic dictionary library. When people read English-Chinese dictionaries, they first read new words in alphabetical order, followed by Chinese explanations, so they know the meaning and usage of the word. The computer uses the same method when using the theme. The computer first scans the account dictionary to find the required account code. The Chinese name of the account is after the account code, account start, opening balance, and final balance. Data sources include: composite account database, construction cost of each workshop, auxiliary production cost allocation table, finished products, product completion degree inventory table, etc.

A complete auto company financial management database team should look like a team with complementary expertise and complementary background, because in fact, it is rare to see a member with all skills. Therefore, team success requires complementary professional skills. Therefore, members of a complete financial management database team must have different backgrounds, ages, genders, experiences and educational backgrounds. It provides the entire team with all the skills they want. In addition, in order to make every member of the team have relationship skills, in the team that often wins, the player who scores goals and the player who helps will be rewarded. The players who help will be rewarded because they have good interpersonal skills, and they use these skills to lead the whole team to victory. Encourage each member of the complete financial management database team to be responsible for the development of the team and the enterprise; Provide them with training opportunities to teach skills and knowledge in general departments and required professional fields; Team leaders should pay attention to the strengths of each member and effectively utilize and develop their strengths. Reward members who put forward reliable ideas and suggestions; Let each member actively participate and have the opportunity to express their opinions.

The financial management database system of automobile enterprises should first be a complete accounting system with all the functions of manual accounting to effectively overcome the shortcomings of manual accounting. Secondly, a rich knowledge base is needed to support the derivation of various systems, so as to adapt to the changes in the time frame of the management model, and combine the management of the previous stage and the next stage. Through analysis, composition, trend and comparison of plans and quotas, the vertical and horizontal comparison of accounting data is automatically identified, and the results of analysis and comparison are clearly reported by comprehensive use of financial accounting, management, audit, statistics, operational research and other methods. It is the essence of financial management software, which can help managers make timely decisions, adjust plans, and effectively manage plans.

If auto enterprises want to achieve long-term sustainable development in the fierce market competition, they must carry out economic activities according to the requirements to maximize the relevant interests of their respective interests. When formulating the financial objectives of the automobile company, it is necessary to take the partners into account, take the maximization of the interests of the partners as the financial objectives of the automobile company, and modify and disassemble the financial objectives according to the actual situation of the automobile company. It is impossible to generalize about the maximization of partners' interests, but we should really pay attention to achieving the balance of partners' interests through specific economic means and the social responsibilities of employees, customers and auto companies. Automobile manufacturers should fulfill their social responsibilities and promote social prosperity. Only through the continuous efforts of automobile enterprises can the real development and long-term progress of automobile enterprises be realized. From the perspective of the design of the financial management database scheme, the design basically adopts a two-step approach, that is, the logical design first, and then the physical design. At the same time, in order to avoid the leakage of image information in the process of image transmission on the network, an image encryption algorithm based on the creation and diffusion key is designed to complete the initial barcode and pixel value processing. In order to make image encryption a reality, the encrypted photos obtained in the original application can completely hide the true content of the original photos, so that it can not directly obtain effective information, and can also well hide the distribution of gray pixels in the original photos, strengthen the ability of the image to resist gray statistical attacks, and provide effective information in the image transmission process.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interests

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Data Availability

Data will be made available on request.

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Design of financial management database for automobile enterprises based on image encryption algorithm

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Abstract

Figures

1 Introduction

2 Related Work

3 Image Encryption Algorithm

3.1 Image encryption algorithm

3.2 Key generation

4 Design Of Financial Management Database For Automobile Enterprises

4.1 Optimization of financial management system of automobile enterprises

4.2 Design of financial management database for automobile enterprises

5 Conclusion

Declarations

References

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