CN109787961B - False flow identification method and device, storage medium and server - Google Patents
False flow identification method and device, storage medium and server Download PDFInfo
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Abstract
A false traffic identification method and device, a storage medium and a server are provided, wherein the identification method comprises the following steps: extracting a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information; counting the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, wherein the IP center geographical position and the coverage radius define the coverage range of the IP address; receiving traffic data to be detected, and determining whether the traffic data to be detected is false traffic or not according to the information pair in the traffic data to be detected and the coverage range of the IP address. By the technical scheme provided by the invention, the false flow and the real flow can be more accurately detected, and the false flow can be screened.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a false flow identification method and device, a storage medium and a server.
Background
In internet Real Time Bidding (RTB) advertisement traffic, there is a lot of false traffic (also called cheat traffic). The false traffic is forged into real traffic by forging cheap cheating means such as an Internet Protocol (IP) address and geographical location information of the false traffic, so as to cheat an advertiser.
The real IP address and its geographical location information are relatively fixed and have a preset matching relationship. However, the IP addresses of spurious traffic and the geographic location information (e.g., latitude and longitude data) associated therewith are typically randomly generated. Thus, part of the false traffic can be detected using the geographical location information of the false traffic, possibly different from the real geographical location information. In the prior art, based on a comparison result of whether there is a difference between geographic location information associated with an IP address of traffic data and geographic location information matched with the IP address, whether the traffic data is false traffic is determined.
However, the preset matching relationship with the geographical location is determined by the IP address, and usually only corresponds to the urban geographical location. For example, the geographic location information matched with one IP address is shanghai, china, and the geographic location information matched with another IP address is beijing, china, and the accuracy of the geographic location is too low. Assuming that the geographical location information associated with the IP address of the real traffic data is a shanghai quiet zone and the geographical location information associated with the IP address of the false traffic for deceiving the advertiser is a purdong new zone of shanghai, the false traffic cannot be identified by using the prior art scheme because the prior art scheme is only accurate to the city level.
Disclosure of Invention
The invention solves the technical problem of how to optimize the false flow identification method so as to more accurately discriminate false flow from real flow.
To solve the above technical problem, an embodiment of the present invention provides a method for identifying false traffic, including: extracting a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information; counting the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, wherein the IP center geographical position and the coverage radius define the coverage range of the IP address; receiving traffic data to be detected, and determining whether the traffic data to be detected is false traffic or not according to the information pair in the traffic data to be detected and the coverage range of the IP address.
Optionally, the identification method further includes: and before counting the plurality of information pairs, filtering the plurality of information pairs according to the preset matching relation between the IP address and the geographic position so as to eliminate the information pairs of which the IP address is not matched with the associated geographic position information.
Optionally, the determining, according to the information pair in the traffic data to be detected and the coverage of the IP address, whether the traffic data to be detected is false traffic includes: for the traffic data to be detected, determining the IP address to be detected and the geographical position information thereof in each information pair; and if the geographic position information of the IP address to be detected falls into the coverage range of the IP address to be detected, determining that the traffic data to be detected is real traffic, and if the geographic position information of the IP address to be detected does not fall into the coverage range of the IP address to be detected, determining that the traffic data to be detected is false traffic.
Optionally, the counting the plurality of information pairs to determine the geographic location of the IP center and the coverage radius corresponding to each IP address includes: dividing the plurality of information pairs according to IP addresses, and dividing the information pairs with the same IP address into the same information cluster; counting the geographic position information associated with the IP address aiming at the IP address in each information cluster to obtain an IP center geographic position corresponding to the IP address, and calculating the distance between the IP center geographic position and the geographic position information in each information pair to obtain a plurality of distance values; fitting a Gaussian distribution curve based on the plurality of distance values to obtain a distance standard deviation of the Gaussian distribution curve; and determining the coverage radius according to the distance standard deviation.
Optionally, the geographic location information in each information pair includes longitude information and latitude information, the IP center geographic location includes longitude information and latitude information, and the calculating a distance between the IP center geographic location and the geographic location information in each information pair includes: and calculating the distance between the geographic position of the IP center and the geographic position information in each information pair by utilizing a longitude and latitude distance formula.
Optionally, the longitude and latitude distance formula is as follows:
wherein d represents the distance between two points, r represents the radius of the earth,
indicating latitude information, λ1、λ2Indicating longitude information.
Optionally, the determining the coverage radius according to the distance standard deviation includes: determining k · σ as the coverage radius, where k represents a preset factor, k >1, and k is a real number, σ represents the distance standard deviation.
In order to solve the above technical problem, an embodiment of the present invention further provides a device for identifying false traffic, including: an extraction module adapted to extract a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information; the statistical module is suitable for performing statistics on the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, and the IP center geographical position and the coverage radius define the coverage range of the IP address; and the determining module is suitable for receiving the traffic data to be detected and determining whether the traffic data to be detected is false traffic or not according to the information pair in the traffic data to be detected and the coverage range of the IP address.
To solve the above technical problem, an embodiment of the present invention further provides a storage medium having stored thereon computer instructions, where the computer instructions execute the steps of the above method when executed.
In order to solve the above technical problem, an embodiment of the present invention further provides a server, including a memory and a processor, where the memory stores computer instructions executable on the processor, and the processor executes the computer instructions to perform the steps of the above method.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a false flow identification method, which comprises the following steps: extracting a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information; counting the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, wherein the IP center geographical position and the coverage radius define the coverage range of the IP address; receiving traffic data to be detected, and determining whether the traffic data to be detected is false traffic or not according to the information pair in the traffic data to be detected and the coverage range of the IP address. Through the technical scheme provided by the embodiment of the invention, the geographic position of the IP center corresponding to each IP address can be counted by utilizing the geographic position information in a large amount of flow data, the coverage range can be determined based on the coverage radius of the IP address, and the adverse effect brought by the statistical error of the geographic position of the IP center is reduced by utilizing the coverage range. Compared with the prior art, the real geographic position matched with the IP address can be more accurately determined by utilizing the coverage range, and further the false flow and the real flow can be more accurately judged so as to discriminate and prevent the false flow.
Further, before counting the plurality of information pairs, the method further includes: and filtering the plurality of information pairs according to the preset matching relation between the IP address and the geographic position so as to eliminate the information pairs of which the IP address is not matched with the associated geographic position information. According to the embodiment of the invention, the invalid information pairs can be filtered by adopting the prior art scheme before counting the plurality of information pairs, so that the method is further favorable for counting the geographic position of the IP center with high accuracy, and lays a foundation for screening the false flow subsequently.
Further, the determining the coverage radius according to the distance standard deviation comprises: determining k · σ as the coverage radius, where k represents a preset factor, k >1, and k is a real number, σ represents the distance standard deviation. According to the embodiment of the invention, the coverage range of the IP address can be defined by using the preset factor and the distance standard deviation, so that adverse effects caused by statistical errors can be effectively reduced, and the false flow discrimination accuracy can be further improved.
Drawings
Fig. 1 is a flow chart illustrating a method for identifying false traffic according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device for identifying false traffic according to an embodiment of the present invention.
Detailed Description
As will be understood by those skilled in the art, as the background art shows, there are a lot of false traffic in internet advertisement traffic, and it is still difficult to accurately identify whether traffic data to be detected is false traffic or real traffic by using the preset matching relationship because the accuracy of the preset matching relationship between the IP address and the geographic location in the prior art is low.
The embodiment of the invention provides a false flow identification method, which comprises the following steps: extracting a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information; counting the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, wherein the IP center geographical position and the coverage radius define the coverage range of the IP address; receiving traffic data to be detected, and determining whether the traffic data to be detected is false traffic or not according to the information pair in the traffic data to be detected and the coverage range of the IP address.
Through the technical scheme provided by the embodiment of the invention, the geographic position of the IP center corresponding to each IP address can be counted by utilizing the geographic position information in a large amount of flow data, the coverage range can be determined based on the coverage radius of the IP address, and the adverse effect brought by the statistical error of the geographic position of the IP center is reduced by utilizing the coverage range. Compared with the prior art, the real geographic position matched with the IP address can be more accurately determined by utilizing the coverage range, and further the false flow and the real flow can be more accurately judged so as to discriminate and prevent the false flow.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
As used herein, the terms "comprising," "including," and the like are to be construed as open-ended terms, i.e., "including/including but not limited to," meaning that additional content can be included as well. In the present disclosure, the term "based on" is "based, at least in part, on".
Fig. 1 is a flowchart illustrating a method for identifying false traffic according to an embodiment of the present invention. The identification method can be used on the side of a computing device, particularly on the side of a server, to detect the authenticity of internet RTB advertising traffic. In particular implementations, the server may be a single server or a server cluster comprised of multiple servers.
Specifically, the identification method may include the steps of:
step S101, extracting a plurality of information pairs from a group of flow data, wherein each information pair comprises an IP address and associated geographical position information;
step S102, counting the plurality of information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, wherein the IP center geographical position and the coverage radius define the coverage range of the IP address;
step S103, receiving the traffic data to be detected, and determining whether the traffic data to be detected is false traffic according to the information pair in the traffic data to be detected and the coverage range of the IP address.
More specifically, in step S101, when a terminal (e.g., a mobile device such as a mobile phone or a Pad) accesses the internet, the terminal typically accesses the internet through a base station or a Wireless Fidelity (Wi-Fi) hotspot of mobile communication, and the server may collect traffic data broadcast by the mobile device. And extracts the information pair of the flow data from each flow data.
The information pair may include an Internet Protocol (IP) address and associated geographical location information. The geographic location information is usually latitude and longitude data, including longitude information and latitude information.
According to the preset matching relationship between the IP address and the geographic position in the prior art, the collected information pairs can be filtered to remove invalid data. The invalid data may be an information pair whose IP address does not match the geographical location information associated with the IP address, or an information pair whose geographical location information is null or whose IP address is null.
For example, the geographic location information associated with the IP address obtained from the information pair extracted from the traffic data is tokyo, japan, and the geographic location information matched with the IP address is nanjing, china, according to the preset matching relationship between the IP address and the geographic location, at this time, the information pair may be determined to be invalid data, and may be rejected.
Those skilled in the art will appreciate that the filtered information pairs are of the order of magnitude of a very large, for example, tens of millions. Taking the example that the geographic position information in the information pair is latitude and longitude data, for each IP address, the number of the latitude and longitude data of the IP address is also very large. For example, for the same mobile device, when the mobile device has a small moving range (for example, the moving range is the same city), the IP addresses of the mobile device may be the same, but since the longitude and latitude data extracted from the traffic data generated by the mobile device may be different during the moving process of the mobile device, a plurality of longitude and latitude data of the same IP address may be obtained.
In step S102, the server may perform statistics on the filtered information pairs to determine an IP center geographical location corresponding to each IP address.
Further, the filtered information pairs can be divided according to different IP addresses. In specific implementation, information pairs with the same IP address can be divided into the same information cluster.
Specifically, the IP address in each information cluster may be counted, that is, the geographical location information associated with the IP address is counted for the IP address in each information cluster, and then the longitude information and the latitude information corresponding to the IP address may be obtained by calculating the mathematical expectation of all the longitude information and the latitude information associated with the IP address, and the longitude information and the latitude information may be used as the geographical location of the IP center of the IP address. The accuracy of the IP-centric geographic location is higher than the geographic location information of IP address matching in the prior art, e.g., the IP-centric geographic location may correspond to neighborhood, road, building information, etc. within a city.
Thereafter, the distance between the IP center geographical location and the geographical location information contained in each information pair in the information cluster can be calculated. Specifically, assuming that the IP address and the longitude and latitude data associated therewith both conform to two-dimensional gaussian distribution, the distance between the geographic position of the IP center and the geographic position information in each information pair can be calculated according to a longitude and latitude distance formula, so as to obtain a plurality of distance values.
Wherein, the longitude and latitude distance formula can be as follows:
where d represents the distance between two points, r represents the radius of the earth, and may be set at 6371 km,
indicating latitude information, λ1、λ2Indicating longitude information.
Further, a gaussian distribution curve may be fitted based on each distance value to obtain a distance standard deviation of the gaussian distribution curve. The distance standard deviation is the minimum coverage radius of the IP center geographical position of the IP address.
In particular implementations, the geographic location is statistical due to the IP center. To reduce the statistical error, k · σ may be determined as the coverage radius to reduce the adverse effect of the statistical error. Wherein k represents a preset factor, k >1, and k is a real number, and σ represents the distance standard deviation.
In practical applications, k may be 3. The k value can be set by those skilled in the art according to actual needs, and is not limited to the above specific scheme.
Based on the IP-centric geographic location and the radius of coverage, a coverage area for the IP address can be defined. After determining the coverage range corresponding to the IP address, the IP center geographic location of the IP address, the distance standard deviation, and the corresponding coverage range may be added to an IP geographic location database.
In step S103, it may be determined whether the traffic data to be detected is a false traffic according to the information pair in the traffic data to be detected and the coverage of the IP address. In a specific implementation, whether the traffic data to be detected is false traffic or not may be determined based on the information pair in the received traffic data to be detected and the IP geographic location database.
Specifically, an information pair including an IP address and associated geographical location information thereof is extracted from the traffic data to be detected. Then, based on the IP geographic location database and the information pair of the traffic data to be detected, it can be determined whether the traffic data to be detected is false traffic.
More specifically, for the traffic data to be detected, determining the IP address to be detected and the geographical location information thereof in each information pair, and if the geographical location information of the IP address to be detected falls within the coverage of the IP address to be detected, determining that the traffic data to be detected is real traffic; otherwise, if the geographic position information of the IP address to be detected does not fall into the coverage range of the IP address to be detected, determining that the traffic data to be detected is false traffic.
As a non-limiting example, after determining the IP address to be detected and its geographic location information (e.g., longitude information and latitude information), the corresponding longitude and latitude data and coverage range may be searched in the IP geographic location database according to the IP address. And then, calculating the distance d between the geographic position information of the IP address to be detected and the geographic position of the IP center of the IP address. When d > k · σ, the IP address to be detected does not fall into the coverage range of the IP address to be detected, and therefore the traffic data to be detected can be determined to be false traffic.
Therefore, by the technical scheme provided by the embodiment of the invention, the geographic position and the coverage area of the IP center of each IP address can be counted, and the accuracy of the geographic position information of the geographic position of the IP center is higher than that of the geographic position information provided by the prior technical scheme, so that the embodiment of the invention can be used for more accurately judging false flow and real flow so as to discriminate and prevent the false flow.
Fig. 2 is a schematic structural diagram of a device for identifying false traffic according to an embodiment of the present invention. The false traffic identification means 2 (for simplicity, referred to as identification means 2) may be implemented by the server side to implement the above-described method solution shown in fig. 1.
Specifically, the identification device 2 may include: an extraction module 21 adapted to extract a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information; a counting module 22, adapted to count the plurality of information pairs to determine an IP center geographic location and a coverage radius corresponding to each IP address, where the IP center geographic location and the coverage radius define a coverage range of the IP address; the determining module 23 is adapted to receive traffic data to be detected, and determine whether the traffic data to be detected is false traffic according to the information pair in the traffic data to be detected and the coverage range of the IP address.
In a specific implementation, the identification device 2 further includes: the filtering module 24 is adapted to filter the plurality of information pairs according to a preset matching relationship between the IP address and the geographic location before counting the plurality of information pairs, so as to eliminate information pairs in which the IP address is not matched with the associated geographic location information.
In a specific implementation, the determining module 23 includes: the first determining submodule 231 is adapted to determine, for the traffic data to be detected, the IP address to be detected and the geographical location information thereof in each information pair; a second determining submodule 232, configured to determine that the traffic data to be detected is real traffic if the geographic location information of the IP address to be detected falls within the coverage of the IP address to be detected, and determine that the traffic data to be detected is false traffic if the geographic location information of the IP address to be detected does not fall within the coverage of the IP address to be detected.
The statistics module 22 may include: a dividing submodule 221 adapted to divide the plurality of information pairs according to IP addresses, and divide information pairs having the same IP address into the same information cluster; a statistics submodule 222, adapted to perform statistics on the geographic location information associated with the IP address for the IP address in each information cluster to obtain an IP center geographic location corresponding to the IP address, and calculate a distance between the IP center geographic location and the geographic location information in each information pair to obtain a plurality of distance values; a fitting submodule 223 adapted to fit a gaussian distribution curve based on the plurality of distance values to obtain a distance standard deviation of the gaussian distribution curve; a third determination submodule 224 adapted to determine the coverage radius from the distance standard deviation.
In a specific implementation, the geographic location information in each information pair may include longitude information and latitude information, the IP center geographic location may include longitude information and latitude information, and the statistics sub-module 222 is further adapted to calculate the distance between the IP center geographic location and the geographic location information in each information pair by using a longitude and latitude distance formula.
The latitude and longitude distance formula may be as follows:
wherein d represents the distance between two points, r represents the radius of the earth,
indicating latitude information, λ1、λ2Indicating longitude information.
In a specific implementation, the third determining submodule 224 is further adapted to determine k · σ as the coverage radius, where k represents a preset factor, k >1, and k is a real number, σ represents the distance standard deviation.
For more details of the operation principle and the operation mode of the identification device 2, reference may be made to the description in fig. 1, and details are not repeated here.
Further, the embodiment of the present invention further discloses a storage medium, on which computer instructions are stored, and when the computer instructions are executed, the technical solution of the method in the embodiment shown in fig. 1 is executed. Preferably, the storage medium may include a computer-readable storage medium such as a non-volatile (non-volatile) memory or a non-transitory (non-transient) memory. The storage medium may include ROM, RAM, magnetic or optical disks, etc.
Further, an embodiment of the present invention further discloses a server, which includes a memory and a processor, where the memory stores computer instructions capable of being executed on the processor, and when the processor executes the computer instructions, the server executes the technical solution of the method in the embodiment shown in fig. 1.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (7)
1. A method for identifying false traffic, comprising:
extracting a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information;
counting the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, wherein the IP center geographical position and the coverage radius define the coverage range of the IP address; the counting the plurality of information pairs to determine the geographic location and the coverage radius of the IP center corresponding to each IP address comprises: dividing the plurality of information pairs according to IP addresses, and dividing the information pairs with the same IP address into the same information cluster; counting the geographic position information associated with the IP address aiming at the IP address in each information cluster to obtain an IP center geographic position corresponding to the IP address, and calculating the distance between the IP center geographic position and the geographic position information in each information pair to obtain a plurality of distance values; fitting a Gaussian distribution curve based on the plurality of distance values to obtain a distance standard deviation of the Gaussian distribution curve; determining the coverage radius from the distance standard deviation, the determining the coverage radius from the distance standard deviation comprising: determining k-sigma as the coverage radius, wherein k represents a preset factor, k >1, k is a real number, and sigma represents the distance standard deviation;
receiving traffic data to be detected, and determining whether the traffic data to be detected is false traffic according to an information pair in the traffic data to be detected and a coverage range of the IP address, including: for the traffic data to be detected, determining the IP address to be detected and the geographical position information thereof in each information pair; and if the geographic position information of the IP address to be detected falls into the coverage range of the IP address to be detected, determining that the traffic data to be detected is real traffic, and if the geographic position information of the IP address to be detected does not fall into the coverage range of the IP address to be detected, determining that the traffic data to be detected is false traffic.
2. The identification method of claim 1, wherein before counting the plurality of information pairs, further comprising:
and filtering the plurality of information pairs according to the preset matching relation between the IP address and the geographic position so as to eliminate the information pairs of which the IP address is not matched with the associated geographic position information.
3. The method of claim 1, wherein the geographic location information in each pair of information comprises longitude information and latitude information, wherein the IP-centric geographic location comprises longitude information and latitude information, and wherein calculating the distance between the IP-centric geographic location and the geographic location information in each pair of information comprises:
and calculating the distance between the geographic position of the IP center and the geographic position information in each information pair by utilizing a longitude and latitude distance formula.
4. The identification method of claim 3, wherein the latitude and longitude distance formula is as follows:
wherein d represents the distance between two points, r represents the radius of the earth,
indicating latitude information, λ1、λ2Indicating longitude information.
5. An apparatus for identifying false traffic, comprising:
an extraction module adapted to extract a plurality of information pairs from a set of traffic data, each information pair comprising an IP address and its associated geographical location information;
the statistical module is suitable for performing statistics on the information pairs to determine an IP center geographical position and a coverage radius corresponding to each IP address, and the IP center geographical position and the coverage radius define the coverage range of the IP address; the counting the plurality of information pairs to determine the geographic location and the coverage radius of the IP center corresponding to each IP address comprises: dividing the plurality of information pairs according to IP addresses, and dividing the information pairs with the same IP address into the same information cluster; counting the geographic position information associated with the IP address aiming at the IP address in each information cluster to obtain an IP center geographic position corresponding to the IP address, and calculating the distance between the IP center geographic position and the geographic position information in each information pair to obtain a plurality of distance values; fitting a Gaussian distribution curve based on the plurality of distance values to obtain a distance standard deviation of the Gaussian distribution curve; determining the coverage radius from the distance standard deviation, the determining the coverage radius from the distance standard deviation comprising: determining k-sigma as the coverage radius, wherein k represents a preset factor, k >1, k is a real number, and sigma represents the distance standard deviation;
the determining module is adapted to receive traffic data to be detected, and determine whether the traffic data to be detected is false traffic according to an information pair in the traffic data to be detected and a coverage range of the IP address, and includes: for the traffic data to be detected, determining the IP address to be detected and the geographical position information thereof in each information pair; and if the geographic position information of the IP address to be detected falls into the coverage range of the IP address to be detected, determining that the traffic data to be detected is real traffic, and if the geographic position information of the IP address to be detected does not fall into the coverage range of the IP address to be detected, determining that the traffic data to be detected is false traffic.
6. A storage medium having stored thereon computer instructions, which when executed by a processor, perform the steps of the method of any one of claims 1 to 4.
7. A server comprising a memory and a processor, the memory having stored thereon computer instructions executable on the processor, wherein the processor, when executing the computer instructions, performs the steps of the method of any one of claims 1 to 4.
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| CN108810947A (en) * | 2018-05-29 | 2018-11-13 | 浙江每日互动网络科技股份有限公司 | The IP address-based server for differentiating real traffic |
| CN109003137A (en) * | 2018-07-23 | 2018-12-14 | 广州至真信息科技有限公司 | A kind of anti-method and device practised fraud of advertisement |
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