Detection method and device for cheating behavior in e-commerce industry
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A behavior and industry technology, applied in the field of cheating detection in the e-commerce industry, can solve problems such as difficulty in finding
Active Publication Date: 2017-07-07
CHINA MOBILE COMM GRP CO LTD
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Problems solved by technology
This kind of group and large-scale malicious cheating has a huge impact on the normal business behavior of e-commerce, but the current popular cheating detection methods mainly track and analyze the specific operation information of users, and only analyze the single behavior of speculators or It is difficult to detect these deliberate, simulating normal operations, changeable, and cluster cheating behaviors
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Embodiment 1
[0044] The embodiment of the present invention provides a method for detecting cheating in the e-commerce industry, such as figure 1 As shown, the processing flow of the method of this embodiment includes the following steps:
[0045] Step 101, receiving a user analysis request.
[0046] The server of the e-commerce enterprise records the International Mobile Subscriber Identification Number (IMSI), the International Mobile Equipment Identity (IMEI) and the mobile user's international integrated service number of the user terminal that has logged into the server. Identification information of the user terminal such as a network code (Mobile Subscriber International Integrated-Service-Digital-NetworkNumber, MSISDN).
[0047] In the method of this embodiment, the e-commerce company can periodically (the period is Pa) send a user analysis request to the detection device, and the cycle can be daily, weekly, etc., or it can be determined according to the subsidy and fee payment cy...
Embodiment 2
[0091] An embodiment of the present invention provides a detection device for cheating in the e-commerce industry, such as figure 2 As shown, the detection device includes a receiving unit 201, an extraction unit 202, an acquisition unit 203, a division unit 204, and a determination unit 205; wherein
[0092] The receiving unit 201 is configured to receive a user analysis request, wherein the user analysis request includes a detection period and identification information of each user terminal to be analyzed;
[0093] The extraction unit 202 is configured to use the identification information of the user terminal to be analyzed received by the receiving unit 201 as an index to extract the X data record XDR data generated by the user terminal to be analyzed within the detection period;
[0094] The obtaining unit 203 is configured to obtain the location information and operation attribute statistics of the user terminal to be analyzed from the XDR data generated by the user te...
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Abstract
An embodiment of the invention discloses a detection method for cheating behaviors in an e-commerce industry. The detection method comprises the steps of: receiving a user analysis request, regarding identification information of user terminals to be analyzed as an index, and extracting XDR data generated by the user terminals to be analyzed in a detection time period; acquiring position information and operation attribute statistics of the user terminals to be analyzed from the XDR data; dividing the user terminals to be analyzed into a plurality of user terminal groups according to similarities of the position information and the operation attribute statistics of the user terminals to be analyzed; acquiring operation behaviors of each user terminal from the XDR data of the user terminals in the same user terminal group; dividing the same user terminal group into a plurality of user terminal subgroups according to the similarities of the operation behaviors; and determining the user terminals in the user terminal subgroups with the similarities of the operation behaviors greater than a preset threshold value as cheating user terminals. The embodiment of the invention further discloses a detection device for the cheating behaviors in the e-commerce industry.
Description
technical field [0001] The invention relates to the field of data analysis, in particular to a method and device for detecting cheating in the e-commerce industry. Background technique [0002] In recent years, with the further development of communication networks and Internet platforms, e-commerce has flourished, and online to offline (Online To Offline, O2O) services have penetrated into every aspect of users' lives. Subsequently, a series of fraud and cheating behaviors specifically aimed at e-commerce business have emerged. For example, in order to cope with competition, various e-commerce companies have launched a series of subsidies and incentive policies; Or, in order to increase exposure and rank, each online store hires some opportunists to cheat sales volume or increase evaluation value. [0003] The above two behaviors have seriously affected the normal operation of e-commerce companies, and corresponding e-commerce companies have also produced a series of monit...
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