A saas privacy data transmission method, storage medium, device and computer program product of an end-to-end operation and maintenance software and hardware all-in-one machine

Abstract

The application discloses an end-to-end operation and maintenance software and hardware integrated machine SaaS private data transmission method, a storage medium, equipment and a computer program product, which comprises the following steps: collecting log information of SaaS private data transmitted in the end-to-end operation and maintenance software and hardware integrated machine, finding out the transmission link of each piece of SaaS private data from the log information, and classifying the transmission link of the SaaS private data according to the business type; for the transmission link of the SaaS private data of each business type, a highest-anti-destruction transmission link is found out in combination with different types of attack strategies; when the SaaS private data is transmitted in the end-to-end operation and maintenance software and hardware integrated machine, the SaaS private data is encrypted, and the highest-anti-destruction transmission link corresponding to the same business type is used for SaaS private data transmission. The application finds out the highest-anti-destruction transmission link to encrypt and transmit the SaaS private data, thereby improving the security of SaaS private data transmission.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of private data transmission, and particularly relates to a SaaS private data transmission method for an end-to-end operation and maintenance software and hardware all-in-one machine, a storage medium, equipment and a computer program product. BACKGROUND

[0002] With the rapid development of intelligent operation and maintenance, cloud computing technology and big data computing, the demand for data in various industries is increasing rapidly, and the accumulation of central data is continuously improving the requirements for end-to-end operation and maintenance software and hardware all-in-one machine deployment and delivery. The end-to-end operation and maintenance software and hardware all-in-one machine integrates hardware and software resources, simplifies the operation and maintenance process, and greatly improves the operation and maintenance efficiency.

[0003] For the SaaS private data in the end-to-end operation and maintenance software and hardware all-in-one machine, the transmission in the network node faces the risk of interception, tampering or leakage, and the attacker can interfere with the normal communication between the end-to-end operation and maintenance software and hardware all-in-one machine and the user by intercepting, tampering or forging data packets, thereby stealing or destroying the SaaS private data. SUMMARY

[0004] In view of the problems in the prior art, the present application provides a SaaS private data transmission method for an end-to-end operation and maintenance software and hardware all-in-one machine, a storage medium, equipment and a computer program product, which finds the transmission link with the highest invulnerability score on the end-to-end operation and maintenance software and hardware all-in-one machine for encrypted transmission of SaaS private data, and performs SaaS private data tampering judgment at each network node in the invulnerability link to prevent SaaS private data from being tampered with and improve the security of SaaS private data transmission in the end-to-end operation and maintenance software and hardware all-in-one machine.

[0005] To achieve the above technical purpose, the present application adopts the following technical solution: a SaaS private data transmission method for an end-to-end operation and maintenance software and hardware all-in-one machine, specifically comprising the following steps:

[0006] Step S1, collecting log information of SaaS private data transmitted in the end-to-end operation and maintenance software and hardware all-in-one machine, finding out the transmission link of each piece of SaaS private data from the log information, and classifying the transmission link of the SaaS private data according to the business type;

[0007] Step S2, for the transmission link of SaaS private data of each business type, find a transmission link with the highest invulnerability in combination with different types of attack strategies;

[0008] Step S3, when transmitting SaaS private data in the end-to-end operation and maintenance software and hardware all-in-one machine, encrypting the SaaS private data, and transmitting the SaaS private data by using the transmission link with the highest invulnerability corresponding to the same business type.

[0009] Further, step S2 comprises the following sub-steps:

[0010] Step S2.1, calculating the node degree, node betweenness and node clustering coefficient of each node in the transmission link of the SaaS privacy data of each service type under each attack strategy;

[0011] Step S2.2, performing Min-Max normalization processing on each node degree, node betweenness and node clustering coefficient respectively;

[0012] Step S2.3, weighting all normalized node degrees, node betweennesses and node clustering coefficients in the transmission link of each piece of SaaS privacy data to obtain the invulnerability score of the transmission link of each piece of SaaS privacy data;

[0013] Step S2.4, taking the transmission link with the highest invulnerability score in each service type as the transmission link of the service type.

[0014] Further, the attack strategies in step S2 include a flooding attack strategy, a confusion attack strategy, a tampering attack strategy and a large model theft attack strategy.

[0015] Further, the calculation process of the invulnerability score of each piece of SaaS privacy data in step S2.3 is as follows:

[0016]

[0017] wherein, S i represents the invulnerability score of the transmission link of the i-th piece of SaaS privacy data, n represents the number of network nodes in the transmission link of the i-th piece of SaaS privacy data, O j represents the normalized result of the node degree of the j-th network node, a represents the weight coefficient of O j , K j represents the normalized result of the node betweenness of the j-th network node, β represents the weight coefficient of K j , and F j represents the normalized result of the clustering coefficient of the j-th network node, γ represents the weight coefficient of F j .

[0018] Further, step S3 comprises the following sub-steps:

[0019] Step S3.1, performing Base64 encryption on the SaaS privacy data when transmitting the SaaS privacy data in the end-to-end operation software and hardware all-in-one machine;

[0020] Step S3.2, assigning the encrypted SaaS privacy data with a Socket identifier recording the transmission link with the highest invulnerability corresponding to the same business type;

[0021] Step S3.3, transmitting the encrypted SaaS privacy data on the transmission link according to the Socket identifier, and performing an anti-tampering check on the encrypted SaaS privacy data at each network node of the transmission link, if the check passes, transmitting the encrypted SaaS privacy data, otherwise, terminating the transmission.

[0022] Further, the specific process of the anti-tampering check on the encrypted SaaS privacy data in step S3.3 is: deploying a fanotify component on all network nodes of the end-to-end operation software all-in-one machine, when the encrypted SaaS privacy data is transmitted to a certain network node in the transmission link, if the configuration file of the fanotify component changes, forwarding the encrypted SaaS privacy data to an isolation area for virus feature matching, and performing virus feature matching on the changed configuration file of the fanotify component, if neither of them matches the virus feature, continuing the transmission of the encrypted SaaS privacy data; otherwise, terminating the transmission of the encrypted SaaS privacy data.

[0023] Further, the present application also provides a computer readable storage medium storing a computer program, comprising: the computer program enables a computer to execute the processor when the computer program is executed to realize the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine.

[0024] Further, the present application also provides an electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, when the processor executes the computer program, realizing the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine.

[0025] Further, the present application also provides a computer program product, comprising a computer program, characterized in that the computer program is executed by a processor to realize the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine.

[0026] Compared with the prior art, the present application has the following beneficial effects:

[0027] (1) The SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine can obtain the highest anti-destroying score of the transmission link by obtaining the node degree, node betweenness and node clustering coefficient of each node under each attack type, and calculating the anti-destroying score, so as to obtain the transmission link with the highest anti-destroying score as the transmission link of the service type. The three indexes of node degree, node betweenness and node clustering coefficient can comprehensively evaluate the overall performance of the transmission link in the end-to-end operation hardware all-in-one machine from different aspects, not only focusing on the importance of a single node, but also considering its position in the network and the influence of the local environment. In addition, with the change of network topology, regular updating of these indexes can help to continuously monitor and adjust the network configuration, ensuring that it always has good anti-destroying performance. The use of transmission links with high anti-destroying performance can reduce the risk of data leakage caused by link failure or attack. Even if the transmission link is damaged to a certain extent, the continuous transmission and integrity of data can be ensured through redundancy and recovery mechanism, effectively protecting SaaS privacy data from unauthorized access and tampering, and ensuring the integrity and confidentiality of SaaS privacy data.

[0028] (2) The SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine uses the transmission link with the highest anti-destroying score to encrypt the SaaS privacy data, and performs anti-tampering check on the SaaS privacy data through the change of the configuration file of the fanotify component at each network node in the anti-destroying link. Once a file is modified or tampered with, the fanotify component can immediately detect it, realize real-time monitoring and response, and forward the encrypted SaaS privacy data to the isolation area for virus feature matching, which can prevent the virus from spreading to the entire transmission link, ensure the security of SaaS privacy data during transmission, and avoid interference to normal business.

[0029] In summary, the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine greatly improves the security of SaaS privacy data transmission of the end-to-end operation software and hardware all-in-one machine. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 The flowchart of the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine is shown.

[0031] Figure 2 The schematic diagram for finding a transmission link with the highest anti-destroying score is shown. DETAILED DESCRIPTION

[0032] The technical solutions of the present application will be further explained and described below in conjunction with the drawings.

[0033] As Figure 1The flowchart of the SaaS private data transmission method of the end-to-end operation and maintenance software and hardware all-in-one machine of the application, the SaaS private data transmission method specifically comprises the following steps:

[0034] Step S1, collect the log information of the SaaS private data transmitted in the end-to-end operation and maintenance software and hardware all-in-one machine, find out the transmission link of each piece of SaaS private data from the log information, and classify the transmission link of the SaaS private data according to the business type.

[0035] Step S2, for the transmission link of the SaaS private data of each business type, combined with different types of attack strategies, find a transmission link with the highest invulnerability, the transmission link with high invulnerability can reduce the risk of data leakage caused by link failure or attack, even if the transmission link is damaged to a certain extent, the continuous transmission and integrity of the data can be ensured through the redundancy and recovery mechanism, effectively protecting the SaaS private data from unauthorized access and tampering, ensuring the integrity and confidentiality of the SaaS private data; such as Figure 2 , specifically comprising the following sub-steps:

[0036] Step S2.1, calculate the node degree, node betweenness and node clustering coefficient of each node in the transmission link of each business type of SaaS private data under each attack strategy; the attack strategies involved in the application include: flooding attack security strategy, confusion attack strategy, tamper-proof attack strategy and large model anti-theft attack strategy, node degree refers to the number of edges directly connected to the node, in a complex network, the larger the node degree, the tighter the connection between the node and other nodes, the more important its position and role in the network, nodes with higher degree may have higher invulnerability because they have more connection paths; node betweenness refers to the proportion of the number of paths passing through the node in all shortest paths in the network, the larger the node betweenness, the stronger the control of the node in the network, which has an important influence on the propagation and circulation of information; node clustering coefficient refers to the ratio of the actual number of edges between the neighbor nodes of the node to the possible number of edges, the larger the clustering coefficient, the tighter the connection between the neighbor nodes of the node, the greater the local influence of the node in the network, nodes with high clustering coefficient may have stronger local stability and invulnerability because they form a close connection with the surrounding nodes. Through the three indicators of node degree, node betweenness and node clustering coefficient, the overall performance of the transmission link in the end-to-end operation and maintenance hardware all-in-one machine can be comprehensively evaluated from different aspects, not only focusing on the importance of a single node, but also considering its position in the network and the influence of the local environment; and with the change of network topology, regularly updating these indicators can help continuously monitor and adjust the network configuration to ensure that it always has good invulnerability.

[0037] Step S2.2, Min-Max normalization is performed on each node degree, node betweenness and node clustering coefficient respectively;

[0038] Step S2.3, the normalized node degree, node betweenness and node clustering coefficient of all nodes in each SaaS privacy data transmission link are weighted to obtain the invulnerability score of each SaaS privacy data transmission link:

[0039]

[0040] Wherein, S i represents the invulnerability score of the i-th SaaS privacy data transmission link, n represents the number of network nodes in the i-th SaaS privacy data transmission link, O j represents the normalized result of the node degree of the j-th network node, a represents the weight coefficient of O j K j represents the normalized result of the node betweenness of the j-th network node, b represents the weight coefficient of K j F j represents the normalized result of the clustering coefficient of the j-th network node, g represents the weight coefficient of F j .

[0041] Step S2.4, the transmission link with the highest invulnerability score in each service type is taken as the transmission link of the service type.

[0042] Step S3, when transmitting SaaS privacy data in the end-to-end operation software and hardware all-in-one machine, the SaaS privacy data is encrypted, and the transmission link with the highest invulnerability corresponding to the same service type is used for SaaS privacy data transmission, so as to realize the secure transmission of SaaS privacy data transmission; specifically including the following sub-steps:

[0043] Step S3.1, when transmitting SaaS privacy data in the end-to-end operation software and hardware all-in-one machine, the SaaS privacy data is Base64 encrypted, specifically, in the SaaS privacy data transmission process, Base64 is used to convert binary data into ASCII string for transmission. Since Base64 encoding can convert binary data such as pictures, audio, video, etc. into text data, the change is easier to be detected by the configuration file of the fanotify component;

[0044] Step S3.2, the encrypted SaaS privacy data is assigned with a Socket identifier recording the transmission link with the highest invulnerability corresponding to the same service type;

[0045] Step S3.3, the encrypted SaaS privacy data is transmitted on the transmission link according to the Socket identifier, and an anti-tampering check is performed on the encrypted SaaS privacy data at each network node of the transmission link, if the check passes, the encrypted SaaS privacy data is transmitted, otherwise, the transmission is terminated.

[0046] The specific process of tracing the encrypted SaaS privacy data in the application is as follows: deploying a fanotify component on all network nodes of the end-to-end operation software all-in-one machine, when the encrypted SaaS privacy data is transmitted to a certain network node in the transmission link, since the binary data is converted into an ASCII string for text form transmission by using Base64, if the configuration file of the fanotify component changes, it may be that the transmission data is tampered with, or the node server is attacked to cause the configuration file to be tampered with. In order to be able to trace the fault and perform the anti-tampering check in time, the encrypted SaaS privacy data is forwarded to the isolation area for virus feature matching, and the configuration file of the fanotify component that has changed is subjected to virus feature matching, if neither of them matches the virus feature, the transmission of the encrypted SaaS privacy data is continued; otherwise, the transmission of the encrypted SaaS privacy data is terminated. Once a file is modified or tampered with in the transmission process of the SaaS privacy data, the fanotify component can immediately detect it, realize real-time monitoring and response, and forward the encrypted SaaS privacy data to the isolation area for virus feature matching, which can prevent the virus from spreading to the entire transmission link, ensure the security of the SaaS privacy data in the transmission process, and avoid interference to normal business

[0047] In one technical solution of the application, a computer readable storage medium is also provided, which stores a computer program, the computer program causes a computer to execute the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine.

[0048] In one technical solution of the application, an electronic device is also provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, when the processor executes the computer program, the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine is realized.

[0049] In one technical solution of the application, a computer program product is also provided, which includes a computer program, when the computer program is executed by a processor, the SaaS privacy data transmission method of the end-to-end operation software and hardware all-in-one machine is realized.

[0050] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium which can contain or store programs for use by or in connection with an instruction execution system, apparatus or device. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination of the above. More specific examples of computer storage medium can include one or more wires, portable computer disks, hard drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), fiber optics, compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0051] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software manner depends on the specific application and design constraints of the technical solutions. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0052] The above is only the preferred embodiment of the present application, and the protection scope of the present application is not limited to the above-mentioned embodiment. Any technical solution falling within the concept of the present application shall fall within the protection scope of the present application. It should be noted that, for ordinary skilled persons in the art, some improvements and refinements without departing from the principles of the present application shall be considered within the protection scope of the present application.

Claims

1. A SaaS privacy data transmission method for end-to-end operation and maintenance of a hardware-software integrated machine, characterized in that, Specifically comprising the following steps: Step S1, collect the log information of the SaaS privacy data transmitted in the end-to-end operation and maintenance software and hardware all-in-one machine, find out the transmission link of each piece of SaaS privacy data from the log information, and classify the transmission link of the SaaS privacy data according to the business type; Step S2, for the transmission link of the SaaS privacy data of each business type, combined with different types of attack strategies, find a transmission link with the highest invulnerability; including the following sub-steps: Step S2.1, calculate the node degree, node betweenness and node clustering coefficient of each node in the transmission link of the SaaS privacy data of each business type under each attack strategy; Step S2.2, respectively, Min-Max normalization processing is carried out on each node degree, node betweenness and node clustering coefficient; Step S2.3, weighting all normalized node degrees, node betweenness and node clustering coefficients in each transmission link of SaaS privacy data, to get the invulnerability score of each transmission link of SaaS privacy data; Step S2.4, the transmission link with the highest invulnerability score in each business type is taken as the transmission link of the business type; Step S3, when transmitting SaaS privacy data in the end-to-end operation and maintenance software and hardware all-in-one machine, encrypt the SaaS privacy data, and use the transmission link with the highest invulnerability corresponding to the same business type to transmit the SaaS privacy data.

2. The SaaS private data transmission method of an end-to-end operation and maintenance software and hardware all-in-one machine according to claim 1, characterized in that, The attack strategies in step S2 include: flooding attack strategy, confusion attack strategy, tampering attack strategy and large model stealing attack strategy.

3. The SaaS private data transmission method of an end-to-end operation and maintenance software and hardware all-in-one machine according to claim 1, characterized in that, The calculation process of the invulnerability score of each transmission link of SaaS privacy data in step S2.3 is as follows: wherein, represents the invulnerability score of the transmission link of the ith piece of SaaS privacy data, n represents the number of network nodes in the transmission link of the ith piece of SaaS privacy data, represents the normalized result of the node degree of the jth network node, represents the weight coefficient of , represents the normalized result of the node betweenness of the jth network node, represents the weight coefficient of , represents the normalized result of the clustering coefficient of the jth network node, represents the weight coefficient of .

4. The SaaS private data transmission method of an end-to-end operation and maintenance software and hardware all-in-one machine according to claim 3, characterized in that, Step S3 includes the following sub-steps: Step S3.1, when transmitting SaaS privacy data in the end-to-end operation and maintenance software and hardware all-in-one machine, Base64 encrypt the SaaS privacy data; Step S3.2, assign the encrypted SaaS privacy data with a Socket identifier recording the transmission link with the highest invulnerability corresponding to the same business type; Step S3.3, the encrypted SaaS privacy data is transmitted on the transmission link according to the Socket identifier, and the encrypted SaaS privacy data is checked for tampering at each network node on the transmission link, if the check is passed, the encrypted SaaS privacy data is transmitted, otherwise, the transmission is terminated.

5. The SaaS private data transmission method of an end-to-end operation and maintenance software and hardware all-in-one machine according to claim 4, characterized in that, The specific process of checking the encrypted SaaS privacy data for tampering in step S3.3 is: deploying a fanotify component on all network nodes of the end-to-end operation and maintenance software all-in-one machine, when the encrypted SaaS privacy data is transmitted to a certain network node in the transmission link, if the configuration file of the fanotify component changes, the encrypted SaaS privacy data is forwarded to the isolation area for virus feature matching, and the configuration file of the fanotify component that has changed is also subjected to virus feature matching, if neither of them matches the virus feature, continue to transmit the encrypted SaaS privacy data; otherwise, terminate the transmission of the encrypted SaaS privacy data.

6. A computer readable storage medium storing a computer program, characterized in that, It includes: The computer program enables a computer to execute the SaaS privacy data transmission method of the end-to-end operation and maintenance software and hardware integrated machine as claimed in any one of claims 1-5 when executed by a processor.

7. An electronic device, comprising: Comprise: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the SaaS privacy data transmission method of the end-to-end operation and maintenance software and hardware integrated machine as claimed in any one of claims 1-5 when executing the computer program.

8. A computer program product comprising a computer program, characterized in that, The computer program enables a computer to execute the SaaS privacy data transmission method of the end-to-end operation and maintenance software and hardware integrated machine as claimed in any one of claims 1-5 when executed by a processor.

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