Account theft risk identification method and device and prevention and control system

Abstract

The invention provides an account theft risk identification method and device and a prevention and control system. The method comprises the steps that information of a device on which an operation is conducted is collected; identity information of all users of history operations on the device within a preset time period before the operation is obtained; all user identity analysis sites are analyzed, the number of the device user identity analysis sites within the time period is counted, and whether the operation has an account theft risk or not is determined accordingly. The device is provided with a device information collecting module, a user information obtaining module, a user identity analyzing module and an account theft risk evaluation module, and whether a current operation has the account theft risk or not can be determined according to the number of the device user identity analysis sites within the preset time period before the current operation. According to the system, the device which evaluates the risk grade through the number of the user identity analysis sites is adopted, the account theft risk can be identified and processed more efficiently, and a safe network environment can be provided for users.

Description

technical field [0001] The present application relates to network security technology, in particular to a risk identification method, identification device and prevention and control system for account theft. Background technique [0002] While online transactions, mobile payments and other applications bring convenience to users, there are also prominent security risks. If the account is stolen, the user may not only suffer property losses, but may also bear the risk that the account thief uses the stolen account to engage in illegal activities. How to promptly and effectively identify whether an account has been stolen, so as to provide users with a network environment as safe as possible, is an important problem that network application service providers cannot avoid and must solve. In the prior art, many fraud risk identification schemes have been proposed, which will be briefly described with examples below. [0003] One type of solution is to identify the risk of acc...

AI Technical Summary

Problems solved by technology

However, the variable of the number of trading users on the device has poor discrimination and stability. For the normal single-device multi-user transaction situation, this scheme is easy to lead to identification errors

[0005] Misjudgment and missed judgments often occur in other network operation behavior risk identification schemes, and the ability to distinguish the risk of theft is not strong enough, resulting in unsatisfactory overall effects of these schemes

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