CN117196784A - Information processing method, device, equipment, medium and product - Google Patents

Abstract

The application provides an information processing method, an information processing device, information processing equipment, information processing media and information processing products, and relates to the technical field of computers, wherein the information processing method comprises the following steps: acquiring order transaction requests of M users, wherein the order transaction requests are used for submitting order information, and M is a positive integer; acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of the duration of commodity browsing and the number of commodity browsing; carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold; intercepting the order transaction requests with the quantity exceeding the first threshold value received in the second preset time period. By the method, the flow control threshold value can be dynamically determined according to the historical behavior information of the user in the first preset time period, the order transaction request is intercepted by using the first threshold value, the performance influence of a wool party on electronic equipment caused by submitting a large number of order transaction requests can be effectively reduced, and the protection effect on the electronic equipment is improved.

Description

Information processing method, device, equipment, medium and product

Technical Field

The present application relates to the field of computer technologies, and in particular, to an information processing method, apparatus, device, medium, and product.

Background

Wool party refers to a population that utilizes various means and platforms to gain improper benefits, including but not limited to registering account numbers, swipes, malicious ordering, malicious high frequency access, and the like. These actions not only can cause economic losses to enterprises, platforms and users, but also can create server resource burden, making normal clients unusable, and destroying the platform reputation.

In order to prevent the interference of the wool party to the server, the transaction exceeding the threshold value is controlled in a flow control mode at present, so that the normal operation of the server resource is ensured. However, in the interception mode in the prior art, the threshold value is fixed and cannot be flexibly adjusted according to actual conditions.

Disclosure of Invention

The information processing method, the device, the equipment, the medium and the product provided by the application can flexibly adjust the threshold value of flow control when the flow control is carried out, and improve the interception effect of malicious requests.

In a first aspect, an embodiment of the present application provides an information processing method, including:

acquiring order transaction requests of M users, wherein the order transaction requests are used for submitting order information, and M is a positive integer;

acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of duration of commodity browsing and number of commodity browsing;

carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold;

intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period.

In a second aspect, the present application provides an information processing apparatus comprising:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring order transaction requests of M users, the order transaction requests are used for submitting order information, and M is a positive integer;

the second acquisition module is used for acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of the duration of commodity browsing and the number of commodity browsing;

the third acquisition module is used for carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold;

and the interception module is used for intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period.

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory storing computer program instructions;

the processor when executing the computer program instructions implements the information processing method as in any one of the embodiments of the first aspect.

In a fourth aspect, embodiments of the present application provide a computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement an information processing method as in any of the embodiments of the first aspect.

In a fifth aspect, embodiments of the present application provide a computer program product, instructions in which, when executed by a processor of an electronic device, cause the electronic device to perform an information processing method implementing any one of the embodiments of the first aspect described above.

The information processing method, device, equipment, medium and product in the embodiment of the application, wherein the method comprises the following steps: acquiring order transaction requests of M users, wherein the order transaction requests are used for submitting order information, and M is a positive integer; acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of duration of commodity browsing and number of commodity browsing; carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold; intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period. By the method, the flow control threshold (namely the first threshold) can be dynamically determined according to the historical behavior information of the user in the first preset time period, the order transaction request is intercepted by using the first threshold subsequently, the performance influence of a wool party on electronic equipment caused by submitting the order transaction request in a large amount can be effectively reduced, and the protection effect on the electronic equipment is improved.

Drawings

In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are needed to be used in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.

Fig. 1 is a schematic flow chart of an information processing method according to an embodiment of the present application;

fig. 2 is a schematic diagram of the structure of an information processing apparatus according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure. The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.

It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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.

In order to solve the problems in the prior art, the embodiment of the application provides an information processing method, an information processing device, information processing equipment, information processing media and information processing products. The information processing method provided by the embodiment of the application is first described below.

Fig. 1 is a flow chart of an information processing method according to an embodiment of the present application. As shown in fig. 1, the information processing method provided in the embodiment of the present application may specifically include the following steps:

step 101, obtaining order transaction requests of M users, wherein the order transaction requests are used for submitting order information, and M is a positive integer.

The order transaction request is used for submitting order information, for example, a user makes a purchase on a shopping platform, after selecting a good, the order is submitted, and the electronic device receives the order transaction request submitted by the user. The order information may include user identification, commodity name, commodity quantity, commodity price, order submission information, and the like.

It should be noted that, the information processing method in the embodiment of the present application may be set in a filter of an electronic device, and is used for filtering an order transaction request sent by a user and intercepting an order transaction request that does not meet requirements. The electronic device may in particular be a server for processing order transaction requests.

Step 102, obtaining historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of duration of commodity browsing and number of commodity browsing.

The first preset period of time may be set according to practical situations, for example, may be 5 minutes, 10 minutes, or 30 minutes, etc., which is not limited herein. The duration of browsing the merchandise may be: the time length for the user to browse the goods in the order information, or the time length for the user to browse each of the goods on the shopping platform, or the time length for the user to browse the goods of the same kind as the goods in the order information on the shopping platform, etc., are not limited herein.

The number of items the user browses may be: the user browses the number of goods on the shopping platform, or the user browses the number of goods of the same kind as the goods in the order information on the shopping platform, or the like.

And step 103, carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold value.

For example, if the historical behavior information includes a duration of browsing the commodity, the plurality of historical behavior information may be screened according to the duration, and the first threshold may be determined according to the number of the historical behavior information obtained by screening, for example, if the number of the historical behavior information obtained by screening is 1000, 1000 may be used as the first threshold, a preset coefficient may be determined according to the length of a first preset time period, a value obtained by multiplying 1000 by the preset coefficient may be used as the first threshold, where the longer the first preset time period, the larger the preset coefficient, the value of the preset coefficient may be less than 1, or the value of the preset coefficient may be greater than 1, and specifically may be set according to the actual situation, and the method is not limited herein.

The preset coefficient may also be determined according to a date corresponding to the historical behavior information, for example, the date corresponding to the historical behavior information is holiday, and the preset coefficient may be set to a value greater than 1.

And 104, intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period.

The second preset period may be set according to practical situations, for example, may be 5 minutes, 10 minutes, or 30 minutes, etc., which is not limited herein. The second preset time period is located after the first preset time period. After determining the first threshold, the number of received order transaction requests within the second preset time period cannot exceed the first threshold. If the number of the currently received order transaction requests does not exceed the first threshold, the sent order transaction requests can be continuously received, otherwise, the sent order transaction requests are intercepted, so that attacks of a wool party for submitting the order transaction requests in a large number are avoided.

In this embodiment, order transaction requests of M users are obtained, where the order transaction requests are used for submitting order information, and M is a positive integer; acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of duration of commodity browsing and number of commodity browsing; carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold; intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period. By the method, the flow control threshold (namely the first threshold) can be dynamically determined according to the historical behavior information of the user in the first preset time period, the order transaction request is intercepted by using the first threshold subsequently, the performance influence of a wool party on electronic equipment caused by submitting the order transaction request in a large amount can be effectively reduced, and the protection effect on the electronic equipment is improved.

In an embodiment of the present application, the obtaining order transaction requests of M users includes:

receiving order transaction requests of N users, wherein the order transaction requests comprise user identifications of each user, and N is an integer greater than or equal to M;

if it is detected that a first user of the N users does not use the user identifier to log on a shopping platform, or the user identifier is an identifier in a preset blacklist, intercepting order transaction requests of the first user within a third preset time period to obtain order transaction requests of the M users.

Specifically, the user identifier may include one or more of a network address of the electronic device used by the user, an account number of the user logging into the shopping platform, a mobile phone number of the user, and an identification card number of the user.

The third preset time period may be located before the second preset time period, and the third preset time period may be 5 minutes, 10 minutes, or 30 minutes, etc., and may specifically be set according to practical situations, which is not limited herein.

In this embodiment, the received order transaction requests of N users are screened, the order transaction requests that have not logged in the shopping platform using the user identifier are screened, and the order transaction requests of the user identifier in the blacklist are screened, so as to obtain the order transaction requests of M users.

It should be noted that, intercepting the order transaction requests of the first user in the third preset time period may mean that the received order transaction requests of the N users are screened to avoid the next processing of the requests to be screened, so as to consume resources, where the order transaction requests of the N users are acquired in the third preset time period;

intercepting the order transaction requests of the first user in the third preset time period may also mean that after receiving the order transaction requests of the N users, the subsequently received order transaction requests are screened, and the order transaction requests of the N users are acquired before the third preset time period.

The N users may refer to the same user or different users, which is not limited herein.

In this embodiment, by screening the received order transaction requests of N users, the non-compliance requests may be effectively intercepted, and the attack of the wool party may be prevented.

In yet another embodiment of the present application, the obtaining order transaction requests of M users includes:

receiving order transaction requests of U users, wherein the order transaction requests comprise user identifications of each user, and U is an integer greater than or equal to M;

if the times of sending the order transaction requests by the second user in the U users in the unit time are detected to be larger than a second threshold value, intercepting the order transaction requests of the second user in a third preset time period to obtain the order transaction requests of the M users.

Specifically, the user identifier may include one or more of a network address of the electronic device used by the user, an account number of the user logging into the shopping platform, a mobile phone number of the user, and an identification card number of the user.

The third preset time period may be located before the second preset time period, and the third preset time period may be 5 minutes, 10 minutes, or 30 minutes, etc., and may specifically be set according to practical situations, which is not limited herein.

The unit time may be 1 minute, 5 minutes, etc., and may be specifically set according to practical situations, which is not limited herein. The second threshold may be 3 or 5, etc., without limitation.

In this embodiment, the received order transaction requests of the U users are screened, and the order transaction requests of the second user whose number of times of sending the order transaction requests in unit time is greater than a second threshold are screened, so as to obtain the order transaction requests of the M users.

It should be noted that, intercepting the order transaction request of the second user in the third preset time period may mean that the received order transaction requests of the U users are screened to avoid the next processing of the request to be screened, so as to consume resources, where the order transaction requests of the U users are acquired in the third preset time period;

intercepting the order transaction requests of the second user in the third preset time period may also mean that after receiving the order transaction requests of the U users, the subsequently received order transaction requests are screened, and the order transaction requests of the U users are acquired before the third preset time period.

In this embodiment, by screening the received order transaction requests of the U users, the non-compliance requests can be effectively intercepted, and the attack of the wool party can be prevented.

In an embodiment of the present application, the performing statistical analysis according to a plurality of the historical behavior information to obtain a first threshold includes:

screening the duration of browsing commodities in each historical behavior information according to a preset duration interval to obtain at least one target historical behavior information, wherein the duration of browsing commodities of the target historical behavior information is located in the duration interval;

and multiplying the number of the at least one target historical behavior information by a preset coefficient to obtain a first threshold value, wherein the preset coefficient is determined according to a first preset time period.

Specifically, the duration interval may be set according to actual situations, for example, the duration interval may be an interval of 5-10 minutes, historical behavior information of the duration of browsing the commodity, which is not located in the duration interval, is screened out, and historical behavior information of the duration of browsing the commodity, which is located in the duration interval, is used as target historical behavior information, so that historical behavior information of the duration of browsing the commodity, which is too small, is screened out, and wool party behaviors are excluded. Historical behavior information with overlarge commodity browsing duration is screened out, and malicious behaviors can be eliminated.

For example, if the number of the target historical behavior information obtained after the screening is 1000, a value obtained by multiplying 1000 by a preset coefficient may be used as the first threshold, where the longer the first preset period is, the larger the preset coefficient is, the smaller the preset coefficient may be, or the larger the preset coefficient may be, and the value may be, or the larger the preset coefficient may be, and specifically may be set according to the actual situation, and the present application is not limited thereto.

The preset coefficient may also be determined according to a date corresponding to the historical behavior information, for example, the date corresponding to the historical behavior information is holiday, and the preset coefficient may be set to a value greater than 1.

In this embodiment, the duration of commodity browsing in each piece of historical behavior information is screened to obtain at least one piece of target historical behavior information, the product of the number of the target historical behavior information and a preset coefficient is used as a first threshold value to flexibly adjust a flow control threshold value, and then the first threshold value is used to intercept the order transaction request, so that performance influence of a wool party submitting a large number of order transaction requests on electronic equipment can be effectively reduced, and protection effect on the electronic equipment is improved.

In another embodiment of the present application, the screening, according to a preset duration interval, the duration of browsing the commodity in each piece of historical behavior information to obtain at least one piece of target historical behavior information includes:

screening the duration of browsing commodities in each piece of historical behavior information according to a preset duration interval to obtain at least one piece of first historical behavior information, wherein the duration of browsing commodities of the first historical behavior information is located in the duration interval;

filtering the historical behavior information of which the number of browsed commodities in the at least one first historical behavior information is smaller than a third threshold value to obtain at least one target historical behavior information.

The third threshold may be 2 or 3, and may be specifically set according to practical situations, which is not limited herein. Under the condition that the duration of browsing the commodities meets the requirements, whether the number of the browsed commodities meets the requirements or not, namely whether the number of the browsed commodities is larger than or equal to a third threshold value or not is also required to be detected, if yes, the commodities are considered to be normal users, corresponding historical behavior information is reserved, and subsequent analysis is facilitated.

In the embodiment, when historical behavior information is screened, not only the duration of browsing commodities but also the number of browsing commodities are considered, so that the wool party behaviors can be effectively avoided, and the accuracy of intercepting the wool party requests in the follow-up process is improved.

In yet another embodiment of the present application, after the acquiring the historical behavior information of each of the users in the first preset time period, the method further includes:

if the duration of browsing commodities in the second historical behavior information is smaller than a duration threshold and the number of browsing commodities in the second historical behavior information is smaller than a fourth threshold, adding the user identification of the user corresponding to the second historical behavior information into the blacklist, wherein the second historical behavior information is any one of the acquired historical behavior information.

In this embodiment, a blacklist may be set according to the historical behavior information, and a user identifier suspected of having a wool party may be added to the blacklist, so that the subsequent filtering of the order transaction request according to the blacklist is facilitated. It should be noted that, for the user identifier that is erroneously determined to be added to the blacklist, the user may remove the user identifier from the blacklist in a complaint manner.

The duration threshold may be set according to the actual situation, and the duration threshold may be a minimum value of the duration interval, or the duration threshold may be smaller than the minimum value of the duration interval, which is not limited herein. The duration of browsing commodities is smaller than the duration threshold value, the number of browsing commodities is smaller than the fourth threshold value, the possibility that the behavior is a wool party is high, and the user identification of the user corresponding to the historical behavior information meeting the two points is added into the blacklist.

In this embodiment, the user identifier added to the blacklist is determined according to the historical behavior information, and the user identifier suspected of the wool party can be added to the blacklist, so that the subsequent filtering of the order transaction request according to the blacklist is facilitated, and the subsequent intercepting accuracy of the wool party request is improved.

Fig. 2 shows a schematic configuration of an information processing apparatus provided in one embodiment of the present application, and only parts related to the embodiment of the present application are shown for convenience of explanation. Referring to fig. 2, the information processing apparatus 200 may include:

a first obtaining module 201, configured to obtain order transaction requests of M users, where the order transaction requests are used for submitting order information, and M is a positive integer;

a second obtaining module 202, configured to obtain historical behavior information of each user in a first preset period, where the historical behavior information includes at least one of a duration of browsing commodities and a number of browsing commodities;

the third obtaining module 203 is configured to perform statistical analysis according to a plurality of the historical behavior information to obtain a first threshold;

the interception module 204 is configured to intercept order transaction requests received in a second preset time period, where the number of order transaction requests exceeds the first threshold.

In an embodiment of the present application, the first obtaining module 201 includes:

the first receiving sub-module is used for receiving order transaction requests of N users, wherein the order transaction requests comprise user identifications of each user, and N is an integer greater than or equal to M;

and the first interception sub-module is used for intercepting the order transaction requests of the first user within a third preset time period to obtain the order transaction requests of the M users if the first user in the N users is detected to log in the shopping platform without using the user identification or the user identification is the identification in a preset blacklist.

In an embodiment of the present application, the first obtaining module 201 includes:

the second receiving sub-module is used for receiving order transaction requests of U users, wherein the order transaction requests comprise user identifiers of all users, and U is an integer greater than or equal to M;

and the second interception sub-module is used for intercepting the order transaction requests of the second user in a third preset time period to obtain the order transaction requests of the M users if the times of sending the order transaction requests by the second user in the unit time is detected to be larger than a second threshold value.

In an embodiment of the present application, the third obtaining module 203 includes:

the first screening sub-module is used for screening the duration of the browsed commodity in each piece of historical behavior information according to a preset duration interval to obtain at least one piece of target historical behavior information, wherein the duration of the browsed commodity of the target historical behavior information is located in the duration interval;

the first acquisition sub-module is used for multiplying the number of the at least one target historical behavior information by a preset coefficient to obtain a first threshold value, and the preset coefficient is determined according to a first preset time period.

In an embodiment of the present application, the first screening submodule includes:

the first screening unit is used for screening the duration of browsing commodities in each piece of historical behavior information according to a preset duration interval to obtain at least one piece of first historical behavior information, wherein the duration of browsing commodities of the first historical behavior information is located in the duration interval;

and the second screening unit is used for filtering the historical behavior information of which the number of the browsed commodities in the at least one first historical behavior information is smaller than a third threshold value to obtain at least one target historical behavior information.

In an embodiment of the application, the apparatus further comprises:

the adding module is configured to add a user identifier of a user corresponding to the second historical behavior information to the blacklist if a duration of browsing the commodity in the second historical behavior information is less than a duration threshold and the number of browsing the commodity in the second historical behavior information is less than a fourth threshold, where the second historical behavior information is any one of the obtained historical behavior information.

The information processing apparatus 200 provided in the embodiment of the present application can implement each process implemented by the foregoing method embodiment, and in order to avoid repetition, a description is omitted here.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

Fig. 3 shows a schematic hardware structure of an electronic device according to an embodiment of the present application.

The electronic device may comprise a processor 301 and a memory 302 in which program instructions are stored.

The steps of any of the various method embodiments described above are implemented when the processor 301 executes a program.

By way of example, a program may be partitioned into one or more modules/units that are stored in the memory 302 and executed by the processor 301 to accomplish the present application. One or more of the modules/units may be a series of program instruction segments capable of performing specific functions to describe the execution of the program in the device.

In particular, the processor 301 may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 302 may include mass storage for data or instructions. By way of example, and not limitation, memory 302 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. Memory 302 may include removable or non-removable (or fixed) media, where appropriate. Memory 302 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 302 is a non-volatile solid-state memory.

The memory may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.

The processor 301 implements any of the methods of the above embodiments by reading and executing program instructions stored in the memory 302.

In one example, the electronic device may also include a communication interface 303 and a bus 310. The processor 301, the memory 302, and the communication interface 303 are connected to each other through the bus 310 and perform communication with each other.

The communication interface 303 is mainly used to implement communication between each module, device, unit and/or apparatus in the embodiment of the present application.

Bus 310 includes hardware, software, or both that couple the components of the online data flow billing device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 310 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.

In addition, in combination with the method in the above embodiment, the embodiment of the present application may be implemented by providing a storage medium. The storage medium has program instructions stored thereon; the program instructions, when executed by a processor, implement any of the methods of the embodiments described above.

The embodiment of the application further provides a chip, the chip comprises a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running programs or instructions, the processes of the embodiment of the method can be realized, the same technical effects can be achieved, and the repetition is avoided, and the description is omitted here.

It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.

Embodiments of the present application provide a computer program product stored in a storage medium, where the program product is executed by at least one processor to implement the respective processes of the above method embodiments, and achieve the same technical effects, and for avoiding repetition, a detailed description is omitted herein.

It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after appreciating the spirit of the present application.

The functional blocks shown in the above block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer grids such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable information processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable information processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.

Claims (10)

1. An information processing method, characterized in that the method comprises:

acquiring order transaction requests of M users, wherein the order transaction requests are used for submitting order information, and M is a positive integer;

acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of duration of commodity browsing and number of commodity browsing;

carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold;

intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period.

2. The method of claim 1, wherein the obtaining order transaction requests for M users comprises:

receiving order transaction requests of N users, wherein the order transaction requests comprise user identifications of each user, and N is an integer greater than or equal to M;

if it is detected that a first user of the N users does not use the user identifier to log on a shopping platform, or the user identifier is an identifier in a preset blacklist, intercepting order transaction requests of the first user within a third preset time period to obtain order transaction requests of the M users.

3. The method of claim 1, wherein the obtaining order transaction requests for M users comprises:

receiving order transaction requests of U users, wherein the order transaction requests comprise user identifications of each user, and U is an integer greater than or equal to M;

if the times of sending the order transaction requests by the second user in the U users in the unit time are detected to be larger than a second threshold value, intercepting the order transaction requests of the second user in a third preset time period to obtain the order transaction requests of the M users.

4. The method of claim 1, wherein said statistically analyzing based on a plurality of said historical behavior information to obtain a first threshold comprises:

screening the duration of browsing commodities in each historical behavior information according to a preset duration interval to obtain at least one target historical behavior information, wherein the duration of browsing commodities of the target historical behavior information is located in the duration interval;

and multiplying the number of the at least one target historical behavior information by a preset coefficient to obtain a first threshold value, wherein the preset coefficient is determined according to a first preset time period.

5. The method of claim 4, wherein the step of screening the duration of browsing the merchandise in each of the historical behavior information according to the preset duration interval to obtain at least one target historical behavior information includes:

screening the duration of browsing commodities in each piece of historical behavior information according to a preset duration interval to obtain at least one piece of first historical behavior information, wherein the duration of browsing commodities of the first historical behavior information is located in the duration interval;

filtering the historical behavior information of which the number of browsed commodities in the at least one first historical behavior information is smaller than a third threshold value to obtain at least one target historical behavior information.

6. The method of claim 2, wherein after said obtaining historical behavior information for each of said users over a first predetermined period of time, said method further comprises:

if the duration of browsing commodities in the second historical behavior information is smaller than a duration threshold and the number of browsing commodities in the second historical behavior information is smaller than a fourth threshold, adding the user identification of the user corresponding to the second historical behavior information into the blacklist, wherein the second historical behavior information is any one of the acquired historical behavior information.

7. An information processing apparatus, characterized in that the apparatus comprises:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring order transaction requests of M users, the order transaction requests are used for submitting order information, and M is a positive integer;

the second acquisition module is used for acquiring historical behavior information of each user in a first preset time period, wherein the historical behavior information comprises at least one of the duration of commodity browsing and the number of commodity browsing;

the third acquisition module is used for carrying out statistical analysis according to the plurality of historical behavior information to obtain a first threshold;

and the interception module is used for intercepting the order transaction requests with the quantity exceeding the first threshold value received in a second preset time period.

8. An electronic device, the device comprising: a processor and a memory storing computer program instructions;

the processor, when executing the computer program instructions, implements the information processing method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon computer program instructions which, when executed by a processor, implement the information processing method according to any of claims 1-6.

10. A computer program product, characterized in that instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the information processing method according to any of claims 1-6.