Emc IP Holding Company LLC

Emc Corporation

Harel Efraim

Triinu Magi Shaashua

Alon Kaufman

Ayelet Levin

Ayelet Biger Levin

Triinu Magi

An improved technique identifies risky transactions by mapping raw user location data to a particular cell in a fixed grid. Along these lines, when a user initiates a transaction with a service provider over a mobile device, the service provider collects raw location data such as a latitude and longitude for the user and transmits the location data to an adaptive authentication server. The adaptive authentication server then accesses a fixed set of geographical areas overlaid on a map of the Earth. For example, the geographic areas can correspond to square cells whose corners are defined by selected latitudes and longitudes. The adaptive authentication server finds a particular geographical area which contains the latitude and longitude for the user. Based on an identifier of the particular geographical area, the adaptive authentication server assigns a risk score to the transaction.

Method of defining the user's geographic areas for risk assessment purposes in mobile channels

A technique identifies risky transactions by mapping raw user location data to a particular cell in a fixed grid. Along these lines, when a user initiates a transaction with a service provider over a mobile device, the service provider collects raw location data such as a latitude and longitude for the user and transmits the location data to an adaptive authentication server. The adaptive authentication server then accesses a fixed set of geographical areas overlaid on a map of the Earth. The adaptive authentication server finds a particular geographical area which contains the latitude and longitude for the user. The adaptive authentication server also obtains information in connection with previous transactions in the particular geographical area using the identifier of the particular geographical area to obtain the information. Based on this information, the adaptive authentication server determines the riskiness of the particular geographical area. Based on the riskiness, the adaptive authentication server assigns a risk score to the transaction.

Identifying risky transactions

An improved technique tracks errors in collecting geolocation data associated with a transaction. Along these lines, an adaptive authentication engine stores information indicative of a failure to collect geolocation data associated with the transaction. In particular, this information takes the form of a geolocation collection state; the adaptive authentication engine stores such a state in a field of a database that contains historical transaction information. If a service provider failed to collect geolocation information for a transaction, the adaptive authentication engine stores a 'Fail' value in the geolocation collection state field of the database entry associated with the transaction. Adaptive authentication techniques may then correlate such 'Fail' values with other field values such as time of submission and device type. The result of such a correlation is to build a risk model based on geolocation collection error which the risk engine may then use to compute risk score.

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Harel Efraim