Click fraud detection
First Claim
1. A computer-implemented method for detecting click fraud, the method comprising:
- determining a subset of activity data from a stored set of activity data, the set of activity data comprising data indicative of visits to one or more websites during a period of time, and the subset of activity data comprising data indicative of visits to the one or more websites during a portion of the period of time;
comparing statistical information about the set of activity data to statistical information about the subset of activity data, wherein the statistical information about the set of activity data comprises a comparison of unpaid referrals in the set of activity data to paid referrals in the set of activity data, and wherein the statistical information about the subset of activity data comprises a comparison of unpaid referrals in the subset of activity data to paid referrals in the subset of activity data; and
assessing whether click fraud is present based at least in part on the comparison of the statistical information about the set of activity data to the statistical information about the subset of activity data.
2 Assignments
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Accused Products
Abstract
Systems and methods for detecting instances of click fraud are disclosed. Click fraud occurs when, for example, a user, malware, bot, or the like, clicks on a pay per click advertisement (e.g., hyperlink), a paid search listing, or the like without a good faith interest in the underlying subject of the hyperlink. Such fraudulent clicks can be expensive for an advertising sponsor. Statistical information, such as ratios of unpaid clicks to pay per clicks, are extracted from an event database. The statistical information of global data is used as a reference data set to compare to similar statistical information for a local data set under analysis. In one embodiment, when the statistical data sets match relatively well, no click fraud is determined to have occurred, and when the statistical data sets do not match relatively well, click fraud is determined to have occurred.
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Citations
20 Claims
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1. A computer-implemented method for detecting click fraud, the method comprising:
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determining a subset of activity data from a stored set of activity data, the set of activity data comprising data indicative of visits to one or more websites during a period of time, and the subset of activity data comprising data indicative of visits to the one or more websites during a portion of the period of time; comparing statistical information about the set of activity data to statistical information about the subset of activity data, wherein the statistical information about the set of activity data comprises a comparison of unpaid referrals in the set of activity data to paid referrals in the set of activity data, and wherein the statistical information about the subset of activity data comprises a comparison of unpaid referrals in the subset of activity data to paid referrals in the subset of activity data; and assessing whether click fraud is present based at least in part on the comparison of the statistical information about the set of activity data to the statistical information about the subset of activity data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system for detecting click fraud, comprising:
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one or more memories configured to store a set of activity data; and one or more computing devices configured to; determine a subset of activity data from the set of activity data, the set of activity data comprising data indicative of visits to one or more websites during a period of time, and the subset of activity data comprising data indicative of visits to the one or more websites during a portion of the period of time, compare statistical information about the set of activity data to statistical information about the subset of activity data, wherein the statistical information about the set of activity data comprises a comparison of unpaid referrals in the set of activity data to paid referrals in the set of activity data, and wherein the statistical information about the subset of activity data comprises a comparison of unpaid referrals in the subset of activity data to paid referrals in the subset of activity data, and assess whether click fraud is present based at least in part on the comparison of the statistical information about the set of activity data to the statistical information about the subset of activity data. - View Dependent Claims (10, 11, 12, 13)
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14. A computer readable medium having instructions stored thereon for detecting click fraud, the instructions comprising:
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instructions to determine a subset of activity data from a stored set of activity data, the set of activity data comprising data indicative of visits to one or more websites during a period of time, and the subset of activity data comprising data indicative of visits to the one or more websites during a portion of the period of time; instructions to compare statistical information about the set of activity data to statistical information about the subset of activity data, wherein the statistical information about the set of activity data comprises a comparison of unpaid referrals in the set of activity data to paid referrals in the set of activity data, and wherein the statistical information about the subset of activity data comprises a comparison of unpaid referrals in the subset of activity data to paid referrals in the subset of activity data; and instructions to assess whether click fraud is present based at least in part on the comparison of the statistical information about the set of activity data to the statistical information about the subset of activity data. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification