CN116151627A - Business wind control method and device, storage medium and electronic equipment - Google Patents
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Abstract
The specification discloses a method, a device, a storage medium and electronic equipment for business wind control, which are used for acquiring business data and determining data to be sent according to the business data; and determining risk-free data from the data to be transmitted, and determining the rest data except the risk-free data in the data to be transmitted. The risk-free data is data which does not cause leakage of service data after being sent to a receiver. According to the service data, determining a first information entropy, and according to the service data and the residual data, determining a second information entropy, wherein the first information entropy is used for representing the information quantity required by acquiring the full-quantity service data under the condition that the receiver does not acquire the residual data, and the second information entropy is used for representing the information quantity required by the receiver to acquire the full-quantity service data after acquiring the residual data. And determining wind control information entropy according to the first information entropy and the second information entropy, and executing service wind control, wherein the wind control information entropy is used for representing the information quantity of leaked service data after the data to be sent are sent to a receiver.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and apparatus for service wind control, a storage medium, and an electronic device.
Background
With the rapid development of internet technology, protection of private data and business wind control are receiving more and more attention from the public. Under the drive, related technologies such as federal learning, multiparty security calculation and the like are introduced, and through the technologies, the occurrence of private data leakage of users can be reduced as much as possible under the condition of realizing business purposes.
However, in the process of executing the service based on federal learning, multiparty security computing and other related technologies, private data leakage still exists, so how to effectively wind control the service executed based on these related technologies is a problem to be solved.
Disclosure of Invention
The specification provides a method, a device, a storage medium and electronic equipment for business wind control, which are used for solving the problem of effectively wind controlling executed business when each participant participates in federal learning or multiparty security calculation.
The technical scheme adopted in the specification is as follows:
the specification provides a method for business wind control, which comprises the following steps:
acquiring service data;
determining data to be transmitted according to the service data;
determining risk-free data from the data to be sent, and determining the rest data except the risk-free data in the data to be sent, wherein the risk-free data is data which does not cause the leakage of the service data after being sent to a receiver;
determining a first information entropy according to the service data, and determining a second information entropy according to the service data and the residual data, wherein the first information entropy is used for representing the information quantity required by acquiring the total quantity of the service data under the condition that the receiving party does not acquire the data to be transmitted, and the second information entropy is used for representing the information quantity required by acquiring the total quantity of the service data after acquiring the data to be transmitted;
determining a wind control information entropy according to the first information entropy and the second information entropy, wherein the wind control information entropy is used for representing the information quantity of the leaked service data after the data to be sent are sent to a receiver;
and executing service wind control according to the wind control information entropy.
Optionally, determining risk-free data from the data to be sent specifically includes:
and determining data which is contained in the data to be transmitted and is obtained by encrypting part of the service data through a preset security protocol as risk-free data.
Optionally, determining risk-free data from the data to be sent specifically includes:
and determining the data obtained by encrypting part of the service data by using the private key contained in the data to be transmitted as risk-free data.
Optionally, determining risk-free data from the data to be sent specifically includes:
and determining the data obtained by masking part of the service data by using the random number contained in the data to be transmitted as risk-free data.
Optionally, determining the first information entropy according to the service data, and determining the second information entropy according to the service data and the residual data specifically includes:
adding the random number into the service data, and determining updated service data;
determining a first information entropy according to the updated service data;
and determining a second information entropy according to the updated service data and the residual data.
Optionally, determining risk-free data from the data to be sent specifically includes:
determining data with a deduction relation from the data to be transmitted;
and determining the data which is contained in the data to be transmitted and can be deduced based on the deduction relation as risk-free data.
The present specification provides a device for service wind control, including:
the acquisition module is used for acquiring service data;
the first determining module is used for determining data to be sent according to the service data;
the second determining module is used for determining risk-free data from the data to be sent and determining the rest data except the risk-free data in the data to be sent, wherein the risk-free data is data which does not cause the leakage of the service data after being sent to a receiver;
the third determining module is configured to determine a first information entropy according to the service data, and determine a second information entropy according to the service data and the remaining data, where the first information entropy is used for characterizing an information amount required for obtaining a full amount of the service data when the receiving party does not obtain the data to be sent, and the second information entropy is used for characterizing an information amount required for obtaining the full amount of the service data after the receiving party obtains the data to be sent;
a fourth determining module, configured to determine, according to the first information entropy and the second information entropy, a wind control information entropy, where the wind control information entropy is used to characterize an information amount of the service data that is leaked after the data to be sent is sent to a receiver;
and the execution module is used for executing business wind control according to the wind control information entropy.
Optionally, the second determining module is specifically configured to determine, as risk-free data, data obtained by encrypting a portion of the service data through a preset security protocol, where the data is included in the data to be sent.
Optionally, the second determining module is specifically configured to determine, as risk-free data, data obtained by encrypting a portion of the service data using a private key, where the data is included in the data to be sent.
Optionally, the second determining module is specifically configured to determine, as risk-free data, data obtained by masking a portion of the service data with a random number included in the data to be sent.
Optionally, the third determining module is specifically configured to add the random number to the service data, and determine updated service data; determining a first information entropy according to the updated service data; and determining a second information entropy according to the updated service data and the residual data.
Optionally, the second determining module is specifically configured to determine data with a derivation relationship from the data to be sent; and determining the data which is contained in the data to be transmitted and can be deduced based on the deduction relation as risk-free data.
The present specification provides a computer readable storage medium storing a computer program which when executed by a processor implements the method of business wind control described above.
The present specification provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of business wind control described above when executing the program.
The above-mentioned at least one technical scheme that this specification adopted can reach following beneficial effect:
in the service wind control method provided by the specification, service data is acquired, data to be transmitted is determined according to the service data, risk-free data is determined from the data to be transmitted, and residual data except the risk-free data in the data to be transmitted is determined, wherein the risk-free data is data which does not cause service data leakage after being transmitted to a receiver. According to the service data, determining a first information entropy, and according to the service data and the residual data, determining a second information entropy, wherein the first information entropy is used for representing the information quantity required by acquiring the full-quantity service data under the condition that the receiver does not acquire the residual data, and the second information entropy is used for representing the information quantity required by the receiver to acquire the full-quantity service data after acquiring the residual data. And determining wind control information entropy according to the first information entropy and the second information entropy, and executing service wind control, wherein the wind control information entropy is used for representing the information quantity of leaked service data after the data to be sent is sent to a receiver.
According to the method, the execution of the service can be effectively controlled according to the determined data size of the service data which is possibly leaked after the data to be sent is sent to the receiver. In addition, when the data size of the service data which can be leaked by the sender is calculated, risk-free data which cannot cause the service data to be leaked after the data to be sent are sent to the receiver is removed, so that the accuracy of the determined information amount (namely wind control information entropy) leaked by the sender when the data to be sent are sent can be ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the specification, illustrate and explain the exemplary embodiments of the present specification and their description, are not intended to limit the specification unduly. In the drawings:
fig. 1 is a schematic flow chart of a method for business wind control provided in the present specification;
FIG. 2 is a schematic diagram of an apparatus for a method of business air control provided in the present specification;
fig. 3 is a schematic diagram of an electronic device corresponding to fig. 1 provided in the present specification.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present specification more apparent, the technical solutions of the present specification will be clearly and completely described below with reference to specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present specification. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.
The following describes in detail the technical solutions provided by the embodiments of the present specification with reference to the accompanying drawings.
Fig. 1 is a flow chart of a method for business wind control provided in the present specification, which includes the following steps:
s100: and acquiring service data.
S102: and determining data to be transmitted according to the service data.
In the prior art, a large amount of data interaction may need to be performed between each participant in the processes of federal learning and multiparty security calculation to execute a service, and private data of each participant may be leaked in the process of transmitting data to other participants by one participant.
The execution subject of the application may be a terminal device used by each participant in a multiparty secure data transmission scene such as multiparty secure computation and federal learning, or may be a server, where the terminal device may include a mobile device such as a mobile phone or a tablet computer. For convenience of explanation, a method for service wind control provided in the present application will be described below by taking a terminal device as an execution body.
In practical application, many participants exist in the federal learning and multiparty security calculation process, according to the transmission direction of data, the participants can be divided into a sender and a receiver, and when the sender sends data to the receiver to process the service, the execution of the service needs to be controlled pneumatically.
Specifically, the terminal device used by the sender may acquire local service data, where the service data is private service data of the sender, and other participants cannot learn. After the service data is obtained, based on the service data, the terminal device can determine part of the data from the service data according to rules agreed by each participant, and then perform data processing (such as encryption processing) on the part of the data to obtain data to be sent, and the terminal device used by the subsequent sender can send the determined data to be sent to the receiver.
S104: and determining risk-free data from the data to be transmitted, and determining the rest data except the risk-free data in the data to be transmitted, wherein the risk-free data is data which does not cause the leakage of the service data after being transmitted to a receiver.
In order to determine the amount of information that may be leaked when the terminal device of the sender sends the data to be sent, it is necessary to assume that the receiver is a party with a problem (i.e. not trusted), and after the sender sends the data to be sent, the receiver may attempt to infer the total amount of service data of the sender according to the data to be sent, where the sender may have a certain risk of information leakage.
Therefore, the terminal device used by the sender needs to estimate the data size of the leaked service data of the sender according to the service data and the data to be sent, and then execute service wind control according to the determined data size of the leaked service data of the sender.
In this specification, the terminal device used by the sender may determine, according to the service data, a first information entropy, where the first information entropy is used to characterize an amount of information required to learn the full amount of service data assuming that the receiver does not acquire the data to be sent. Further, the terminal device used by the sender may further determine, according to the service data and the data to be sent, a second information entropy, where the second information entropy is used to characterize an information amount required for obtaining the full service data after the receiver obtains the data to be sent.
And then, the terminal equipment used by the sender can determine the wind control information entropy according to the determined first information entropy and the determined second information entropy, wherein the wind control information entropy is used for representing the information quantity of the leaked service data after the data to be sent is sent to the receiver.
The specific formula is referred to as follows:
wherein,,representing business data->Representing data to be transmitted,/>Is wind control information entropy->For the first information entropy, the characterization assumes that the amount of information needed to learn the full traffic data without the receiving party acquiring the data to be transmitted,and characterizing the information quantity required by the receiver for acquiring the full traffic data after acquiring the data to be transmitted as the second information entropy.
In this way, the terminal device used by the sender can estimate the amount of information that the service data of the sender is leaked after the sender sends the data to be sent to the receiver, and after the wind control information entropy is determined, the subsequent terminal device can execute service wind control according to the wind control information entropy.
However, in practical applications, some interactive data in federal learning and multiparty security computation may be encrypted or derived from other data, and such data may not cause leakage of service data, and should not participate in the calculation process of the entropy of wind control information. Therefore, when the wind control information entropy is determined, the terminal equipment used by the sender can reject the risk-free data from the data to be sent, so that the finally determined wind control information entropy is more accurate.
In this specification, risk-free data that does not cause leakage of service data after being determined to be transmitted to a receiving side from data to be transmitted can be classified into four cases.
Specifically, the terminal device may determine, as the risk-free data, data obtained by encrypting part of the service data through a preset security protocol, which is included in the data to be transmitted.
The preset security protocol may refer to a security protocol adopted in federal learning or multiparty security calculation, such as MPC protocol (Mobility Personal Computer, MPC), etc., and the specification does not limit the type of the protocol.
For example, if the part of the data included in the data to be transmitted is obtained by encrypting the terminal device used by the transmitting side through the security protocol, the terminal device may determine the part of the data included in the data to be transmitted as risk-free data.
Of course, the terminal device may also determine, as risk-free data, data obtained by encrypting part of the service data using the private key, which is included in the data to be transmitted.
For example, if the part of the data included in the data to be sent is obtained by encrypting the part of the service data by the terminal device through some encryption algorithms, the terminal device may determine the part of the data included in the data to be sent as risk-free data.
The encryption algorithm may include: hash Message authentication algorithms (Hash-based Message Authentication Code, HAMC), message digest algorithms (Message-Digest Algorithm MD, MD 5), and the like. The present description is not limited to the specific encryption algorithm employed.
It should be noted that, when the terminal device uses the private key to perform a part of service data, the private key must be held by the sender alone, so that it can be ensured that the risk-free data determined in this way will not leak service data after being acquired by the receiver.
In addition, the terminal device may determine the data obtained by masking a part of the service data with the random number included in the data to be transmitted as risk-free data.
For example, if part of the data to be transmitted is obtained by adding or subtracting a random number to or from part of the service data by the terminal device, the masking may be regarded as an encryption method because the random number is held only by the sender, and the data obtained by masking part of the service data using the random number may be determined to be risk-free data.
It should be noted that, since the encryption using the random number multiple times is not secure, the terminal device can only perform the encryption using the random number once. When the terminal device uses the random number to mask part of the service data, the random number is only held by the sender, and can be regarded as private data of the sender, and the terminal device can add the random number into the service data to determine updated service data. The subsequent terminal device may determine the first information entropy according to the updated service data, and determine the second information entropy according to the updated service data and the data to be transmitted.
In addition, the terminal device may determine data having a derivation relationship from the data to be transmitted, and determine data that is included in the data to be transmitted and can be derived based on the derivation relationship as risk-free data.
For example, if the data to be transmitted includes A, B, C data, there are three deductions as follows: a=b+c, from which a can be derived, then the terminal device can determine a as risk-free data.
The above-described derivation relation is only an example, and if there is a similar derivation relation for the data included in the data to be transmitted, the terminal device may determine the data included in the data to be transmitted that can be deduced based on the derivation relation as risk-free data.
S106: according to the service data, a first information entropy is determined, and according to the service data and the residual data, a second information entropy is determined, wherein the first information entropy is used for representing the information quantity required by acquiring the total service data under the condition that the receiving party does not acquire the data to be transmitted, and the second information entropy is used for representing the information quantity required by acquiring the total service data after the receiving party acquires the data to be transmitted.
S108: and determining wind control information entropy according to the first information entropy and the second information entropy, wherein the wind control information entropy is used for representing the information quantity of the leaked service data after the data to be sent are sent to a receiver.
S110: and executing service wind control according to the wind control information entropy.
By the method, after the risk-free data and the residual data except the risk-free data are determined from the data to be sent, the terminal equipment used by the sender can more accurately determine the second information entropy based on the service data and the residual data, and further, according to the first information entropy and the second information entropy, the wind control information entropy is determined and used for representing the information quantity of the leaked service data after the data to be sent is sent to the receiver.
The specific formula is referred to as follows:
wherein,,representing business data->Representing the remaining data of the data to be transmitted, < +.>Is the entropy of the wind control information,is a first information entropy characterizing the amount of information needed to learn the full traffic data assuming that the receiver does not acquire the data to be transmitted,/i>Is a second information entropy, which represents the amount of information required for assuming that the receiving side knows the full-size service data of the transmitting side after acquiring the remaining data.
For example, assuming that the amount of information required for the full-size service data of the sender is 100MB in the case where the receiver does not acquire the data to be sent, and the amount of information required for the full-size service data of the sender is 30MB after the receiver acquires the remaining data in the data to be sent, the amount of information that the service data is leaked after the sender transmits the data to be sent to the receiver is 70MB.
It should be noted that, the foregoing example is described based on the size of the specific data amount leaked by the sender, and in this specification, the terminal device may also determine a first information entropy and a second information entropy according to the service data of the sender and the data to be sent, and then determine, according to the first information entropy and the second information entropy, a wind control information entropy for characterizing that the receiver obtains the information amount required by the full-amount service data after obtaining the data to be sent.
After the wind control information entropy is determined in the mode, the terminal equipment can execute wind control based on the information quantity of the leaked service data after the sender sends the data to be sent to the receiver, and further based on the wind control information entropy.
Specifically, after the terminal device determines the wind control information entropy, the wind control information entropy may be displayed to the user, so that the user decides whether to send the data to be sent to the receiver based on the wind control information entropy.
In addition, the terminal device may perform service wind control in other manners. For example, if the terminal device determines, through the wind control information entropy, that the amount of information leaked by the sender exceeds a preset threshold, or determines that the wind control information entropy does not fall within a preset safety information entropy range, the terminal device used by the sender may prevent sending the data to be sent.
It should be noted that, in the process of federal learning and multiparty security calculation, there may be a case where one party transmits data and multiple parties receive data, so the above-mentioned receiving party in the present specification may be multiple receiving parties, and at this time, the data to be transmitted is the sum of the data transmitted by the transmitting party to all receiving parties.
In this case, it is assumed that a plurality of receivers, after receiving data transmitted from the transmitter respectively, collectively attempt to estimate the total amount of service data of the transmitter from the received data, and at this time, the terminal device used by the transmitter may determine the amount of information that may leak by itself after transmitting the data to be transmitted to the receiver by the service wind control method provided in the present specification.
It should be noted that the method for traffic wind control provided in the present specification may also be used to evaluate the security of a security protocol or an encryption algorithm used in a multiparty secure data transmission scenario (such as multiparty secure computing or federal learning). After determining the information amount leaked by the sender when sending the data to be sent, the terminal device can send the information amount to relevant maintainers or trusted personnel in federal learning or multiparty security calculation, so that the relevant maintainers can evaluate whether the used security protocol or encryption algorithm is safe according to the information amount possibly leaked by the sender, and further adjust the security protocol or encryption algorithm, thereby being beneficial to guaranteeing the security of private data of each participant.
According to the method, a first information entropy used for representing the information quantity required by the full-quantity service data obtained by the receiver under the condition that the receiver does not obtain the data to be transmitted can be determined according to the service data and the data to be transmitted, a second information entropy used for representing the information quantity required by the full-quantity service data obtained by the receiver after the receiver obtains the data to be transmitted is determined, and further, a wind control information entropy used for representing the information quantity leaked by the service data after the data to be transmitted is transmitted to the receiver is determined according to the first information entropy and the second information entropy, and then effective wind control is performed on service execution based on the wind control information entropy.
The method is beneficial to the participants to know the amount of the leaked information after the data to be sent are sent to the receiver by the participants in the process of participating in federal learning or multiparty security calculation, so that the amount of the leaked information is controlled. In addition, when the data size of the service data which can be leaked by the sender is determined, risk-free data which cannot cause the service data to be leaked after the data to be sent are sent to the receiver is removed, so that the accuracy of the determined information amount (namely wind control information entropy) leaked by the sender when the data to be sent are sent can be ensured.
The above method for controlling service wind provided for one or more embodiments of the present disclosure further provides a corresponding device for controlling service wind based on the same concept, as shown in fig. 2.
Fig. 2 is a schematic diagram of a service wind control device provided in the present specification, including:
an acquisition module 200, configured to acquire service data;
a first determining module 202, configured to determine data to be sent according to the service data;
a second determining module 204, configured to determine risk-free data from the data to be sent, and determine remaining data in the data to be sent except for the risk-free data, where the risk-free data is data that does not cause leakage of the service data after being sent to a receiver;
a third determining module 206, configured to determine a first information entropy according to the service data, and determine a second information entropy according to the service data and the remaining data, where the first information entropy is used for characterizing an information amount required for obtaining a full amount of the service data when the receiving side does not obtain the data to be sent, and the second information entropy is used for characterizing an information amount required for obtaining the full amount of the service data when the receiving side obtains the data to be sent;
a fourth determining module 208, configured to determine, according to the first information entropy and the second information entropy, a wind control information entropy, where the wind control information entropy is used to characterize an amount of information that is leaked from the service data after the data to be sent is sent to the receiver;
and the executing module 210 is configured to execute service wind control according to the wind control information entropy.
Optionally, the second determining module 204 is specifically configured to determine, as risk-free data, data that is included in the data to be sent and obtained by encrypting a portion of the service data through a preset security protocol.
Optionally, the second determining module 204 is specifically configured to determine, as risk-free data, data obtained by encrypting a portion of the service data with a private key included in the data to be sent.
Optionally, the second determining module 204 is specifically configured to determine, as risk-free data, data obtained by masking a portion of the service data with a random number included in the data to be sent.
Optionally, the third determining module 206 is specifically configured to add the random number to the service data, and determine updated service data; determining a first information entropy according to the updated service data; and determining a second information entropy according to the updated service data and the residual data.
Optionally, the second determining module 204 is specifically configured to determine data having a derivation relationship from the data to be sent; and determining the data which is contained in the data to be transmitted and can be deduced based on the deduction relation as risk-free data.
The present specification also provides a computer readable storage medium storing a computer program operable to perform a method of business wind control as provided in fig. 1 above.
The present specification also provides a schematic structural diagram of an electronic device corresponding to fig. 1 shown in fig. 3. At the hardware level, as in fig. 3, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile storage, although it may include hardware required for other services. The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to realize the business wind control method of the figure 1. Of course, other implementations, such as logic devices or combinations of hardware and software, are not excluded from the present description, that is, the execution subject of the following processing flows is not limited to each logic unit, but may be hardware or logic devices.
In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable Gate Array, FPGA)) is an integrated circuit whose logic function is determined by the programming of the device by a user. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.
It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present description can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present description is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing is merely an example of the present specification and is not intended to limit the present specification. Various modifications and alterations to this specification will become apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of the present description, are intended to be included within the scope of the claims of the present description.
Claims (14)
1. A method of business wind control, comprising:
acquiring service data;
determining data to be transmitted according to the service data;
determining risk-free data from the data to be sent, and determining the rest data except the risk-free data in the data to be sent, wherein the risk-free data is data which does not cause the leakage of the service data after being sent to a receiver;
determining a first information entropy according to the service data, and determining a second information entropy according to the service data and the residual data, wherein the first information entropy is used for representing the information quantity required by acquiring the total quantity of the service data under the condition that the receiving party does not acquire the data to be transmitted, and the second information entropy is used for representing the information quantity required by acquiring the total quantity of the service data after acquiring the data to be transmitted;
determining a wind control information entropy according to the first information entropy and the second information entropy, wherein the wind control information entropy is used for representing the information quantity of the leaked service data after the data to be sent are sent to a receiver;
and executing service wind control according to the wind control information entropy.
2. The method of claim 1, determining risk-free data from the data to be transmitted, specifically comprising:
and determining data which is contained in the data to be transmitted and is obtained by encrypting part of the service data through a preset security protocol as risk-free data.
3. The method of claim 1, determining risk-free data from the data to be transmitted, specifically comprising:
and determining the data obtained by encrypting part of the service data by using the private key contained in the data to be transmitted as risk-free data.
4. The method of claim 1, determining risk-free data from the data to be transmitted, specifically comprising:
and determining the data obtained by masking part of the service data by using the random number contained in the data to be transmitted as risk-free data.
5. The method of claim 4, determining a first information entropy according to the service data, and determining a second information entropy according to the service data and the remaining data, specifically comprising:
adding the random number into the service data, and determining updated service data;
determining a first information entropy according to the updated service data;
and determining a second information entropy according to the updated service data and the residual data.
6. The method of claim 1, determining risk-free data from the data to be transmitted, specifically comprising:
determining data with a deduction relation from the data to be transmitted;
and determining the data which is contained in the data to be transmitted and can be deduced based on the deduction relation as risk-free data.
7. A business air control device, comprising:
the acquisition module is used for acquiring service data;
the first determining module is used for determining data to be sent according to the service data;
the second determining module is used for determining risk-free data from the data to be sent and determining the rest data except the risk-free data in the data to be sent, wherein the risk-free data is data which does not cause the leakage of the service data after being sent to a receiver;
the third determining module is configured to determine a first information entropy according to the service data, and determine a second information entropy according to the service data and the remaining data, where the first information entropy is used for characterizing an information amount required for obtaining a full amount of the service data when the receiving party does not obtain the data to be sent, and the second information entropy is used for characterizing an information amount required for obtaining the full amount of the service data after the receiving party obtains the data to be sent;
a fourth determining module, configured to determine, according to the first information entropy and the second information entropy, a wind control information entropy, where the wind control information entropy is used to characterize an information amount of the service data that is leaked after the data to be sent is sent to a receiver;
and the execution module is used for executing business wind control according to the wind control information entropy.
8. The device of claim 7, wherein the second determining module is specifically configured to determine, as risk-free data, data that is included in the data to be sent and obtained by encrypting a portion of the service data through a preset security protocol.
9. The apparatus of claim 7, wherein the second determining module is specifically configured to determine, as risk-free data, data obtained by encrypting a portion of the service data with a private key included in the data to be transmitted.
10. The apparatus of claim 7, wherein the second determining module is specifically configured to determine, as risk-free data, data obtained by masking a portion of the service data with a random number included in the data to be transmitted.
11. The apparatus of claim 10, wherein the third determining module is specifically configured to add the random number to the service data, and determine updated service data; determining a first information entropy according to the updated service data; and determining a second information entropy according to the updated service data and the residual data.
12. The apparatus of claim 7, wherein the second determining module is specifically configured to determine data having a derivation relation from the data to be transmitted; and determining the data which is contained in the data to be transmitted and can be deduced based on the deduction relation as risk-free data.
13. A computer readable storage medium storing a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-6.
14. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any of the preceding claims 1-6 when executing the program.
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Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117313063A (en) * | 2023-11-30 | 2023-12-29 | 浙江尚链信息科技有限责任公司 | Data response monitoring management method and system based on multiparty security calculation |
Citations (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9166999B1 (en) * | 2014-07-25 | 2015-10-20 | Fmr Llc | Security risk aggregation, analysis, and adaptive control |
US20170124492A1 (en) * | 2015-10-28 | 2017-05-04 | Fractal Industries, Inc. | System for automated capture and analysis of business information for reliable business venture outcome prediction |
WO2019149021A1 (en) * | 2018-02-01 | 2019-08-08 | 阿里巴巴集团控股有限公司 | Data processing method and apparatus for claims settlement service, and electronic device and server |
CN110147967A (en) * | 2019-05-28 | 2019-08-20 | 阿里巴巴集团控股有限公司 | Risk prevention system method and device |
WO2020034751A1 (en) * | 2018-08-14 | 2020-02-20 | 阿里巴巴集团控股有限公司 | Multi-party security computing method and apparatus, and electronic device |
CN111160814A (en) * | 2020-04-01 | 2020-05-15 | 支付宝(杭州)信息技术有限公司 | User risk assessment method, device and system based on multi-party security calculation |
CN111538875A (en) * | 2020-04-27 | 2020-08-14 | 支付宝(杭州)信息技术有限公司 | Service index acquisition method and device and wind control equipment |
CN111966715A (en) * | 2020-08-17 | 2020-11-20 | 支付宝(杭州)信息技术有限公司 | Service processing method, device, electronic equipment and storage medium |
WO2021114820A1 (en) * | 2019-12-12 | 2021-06-17 | 支付宝(杭州)信息技术有限公司 | Method and apparatus for joint risk identification by multiple parties |
WO2021114974A1 (en) * | 2019-12-14 | 2021-06-17 | 支付宝(杭州)信息技术有限公司 | User risk assessment method and apparatus, electronic device, and storage medium |
EP3849132A1 (en) * | 2020-01-10 | 2021-07-14 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method, apparatus for blockchain-based multi-party computation, device and medium |
CN113159781A (en) * | 2021-03-25 | 2021-07-23 | 支付宝(杭州)信息技术有限公司 | Risk detection method and device for protecting private data |
US20210342454A1 (en) * | 2016-06-10 | 2021-11-04 | OneTrust, LLC | Data processing and scanning systems for assessing vendor risk |
WO2022121083A1 (en) * | 2020-12-09 | 2022-06-16 | 南威软件股份有限公司 | Enterprise risk early warning method based on association analysis fp-tree algorithm |
CN114692717A (en) * | 2020-12-31 | 2022-07-01 | 华为技术有限公司 | Tree model training method, device and system |
CN115062299A (en) * | 2022-07-26 | 2022-09-16 | 华控清交信息科技(北京)有限公司 | Security detection method and device for data leakage and electronic equipment |
CN115134067A (en) * | 2022-06-29 | 2022-09-30 | 蚂蚁区块链科技(上海)有限公司 | Method for detecting private data leakage |
CN115174212A (en) * | 2022-07-05 | 2022-10-11 | 北京威努特技术有限公司 | Method for discriminating whether network data transmission is encrypted or not by utilizing entropy technology |
WO2022257723A1 (en) * | 2021-06-07 | 2022-12-15 | 支付宝(杭州)信息技术有限公司 | Risk prevention and control method, apparatus and device |
CN115545720A (en) * | 2022-11-29 | 2022-12-30 | 支付宝(杭州)信息技术有限公司 | Model training method, business wind control method and business wind control device |
CN115640998A (en) * | 2022-10-21 | 2023-01-24 | 杭州安恒信息技术股份有限公司 | Risk assessment method, device, equipment and storage medium |
-
2023
- 2023-04-04 CN CN202310396957.1A patent/CN116151627B/en active Active
Patent Citations (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9166999B1 (en) * | 2014-07-25 | 2015-10-20 | Fmr Llc | Security risk aggregation, analysis, and adaptive control |
US20170124492A1 (en) * | 2015-10-28 | 2017-05-04 | Fractal Industries, Inc. | System for automated capture and analysis of business information for reliable business venture outcome prediction |
US20210342454A1 (en) * | 2016-06-10 | 2021-11-04 | OneTrust, LLC | Data processing and scanning systems for assessing vendor risk |
WO2019149021A1 (en) * | 2018-02-01 | 2019-08-08 | 阿里巴巴集团控股有限公司 | Data processing method and apparatus for claims settlement service, and electronic device and server |
WO2020034751A1 (en) * | 2018-08-14 | 2020-02-20 | 阿里巴巴集团控股有限公司 | Multi-party security computing method and apparatus, and electronic device |
CN110147967A (en) * | 2019-05-28 | 2019-08-20 | 阿里巴巴集团控股有限公司 | Risk prevention system method and device |
WO2021114820A1 (en) * | 2019-12-12 | 2021-06-17 | 支付宝(杭州)信息技术有限公司 | Method and apparatus for joint risk identification by multiple parties |
WO2021114974A1 (en) * | 2019-12-14 | 2021-06-17 | 支付宝(杭州)信息技术有限公司 | User risk assessment method and apparatus, electronic device, and storage medium |
EP3849132A1 (en) * | 2020-01-10 | 2021-07-14 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method, apparatus for blockchain-based multi-party computation, device and medium |
CN111160814A (en) * | 2020-04-01 | 2020-05-15 | 支付宝(杭州)信息技术有限公司 | User risk assessment method, device and system based on multi-party security calculation |
CN111538875A (en) * | 2020-04-27 | 2020-08-14 | 支付宝(杭州)信息技术有限公司 | Service index acquisition method and device and wind control equipment |
CN111966715A (en) * | 2020-08-17 | 2020-11-20 | 支付宝(杭州)信息技术有限公司 | Service processing method, device, electronic equipment and storage medium |
WO2022121083A1 (en) * | 2020-12-09 | 2022-06-16 | 南威软件股份有限公司 | Enterprise risk early warning method based on association analysis fp-tree algorithm |
CN114692717A (en) * | 2020-12-31 | 2022-07-01 | 华为技术有限公司 | Tree model training method, device and system |
CN113159781A (en) * | 2021-03-25 | 2021-07-23 | 支付宝(杭州)信息技术有限公司 | Risk detection method and device for protecting private data |
WO2022257723A1 (en) * | 2021-06-07 | 2022-12-15 | 支付宝(杭州)信息技术有限公司 | Risk prevention and control method, apparatus and device |
CN115134067A (en) * | 2022-06-29 | 2022-09-30 | 蚂蚁区块链科技(上海)有限公司 | Method for detecting private data leakage |
CN115174212A (en) * | 2022-07-05 | 2022-10-11 | 北京威努特技术有限公司 | Method for discriminating whether network data transmission is encrypted or not by utilizing entropy technology |
CN115062299A (en) * | 2022-07-26 | 2022-09-16 | 华控清交信息科技(北京)有限公司 | Security detection method and device for data leakage and electronic equipment |
CN115640998A (en) * | 2022-10-21 | 2023-01-24 | 杭州安恒信息技术股份有限公司 | Risk assessment method, device, equipment and storage medium |
CN115545720A (en) * | 2022-11-29 | 2022-12-30 | 支付宝(杭州)信息技术有限公司 | Model training method, business wind control method and business wind control device |
Non-Patent Citations (4)
Title |
---|
XIANXIAN LI 等: "Information Entropy Differential Privacy: A Differential Privacy Protection Data Method Based on Rough Set Theory", 《2019 IEEE INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, INTL CONF ON CLOUD AND BIG DATA COMPUTING, INTL CONF ON CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/CBDCOM/CYBERSCITECH)》 * |
叶明全;胡学钢;伍长荣;: "垂直划分多决策表下基于条件信息熵的隐私保护属性约简", 山东大学学报(理学版), no. 09 * |
彭长根;丁红发;朱义杰;田有亮;符祖峰;: "隐私保护的信息熵模型及其度量方法", 软件学报, no. 08 * |
王春凯;冯键;: "联邦学习在保险行业的应用研究", 保险职业学院学报, no. 01 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117313063A (en) * | 2023-11-30 | 2023-12-29 | 浙江尚链信息科技有限责任公司 | Data response monitoring management method and system based on multiparty security calculation |
CN117313063B (en) * | 2023-11-30 | 2024-03-22 | 浙江尚链信息科技有限责任公司 | Data response monitoring management method and system based on multiparty security calculation |
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