Abstract: This specification discloses techniques for risk identification. One example method includes receiving, by a client device, a risk identification request identifying a requested service operation and service data associated with the requested service operation; retrieving, by the client device, service data corresponding to the risk identification request; determining, by the client device, service indicator data associated with the service data; analyzing, by the client device, one or more of the service data and the service indicator based on a risk identification rule or a risk identification model to produce a risk result; and determining, by the client device, whether the requested service operation is a high risk operation based at least in part on the risk result.

Abstract: An authentication factor is received, including an authentication key, an account information of a user, and a dynamic time factor. A bound authentication information is generated by using the authentication factor and a device information of a client device that requested the secure offline payment. The bound authentication information is transmitted to a service server system perform an offline payment authorization based on the bound authentication information. In response to a successful offline payment authorization, a graphical identifier is generated for completing the secure offline payment associated with the authentication factor, where the graphical identifier includes the bound authentication information and a dynamic password generated based on the dynamic time factor.

Abstract: This specification discloses techniques for risk identification. One example method includes receiving, by a client device, a risk identification request identifying a requested service operation and service data associated with the requested service operation; retrieving, by the client device, service data corresponding to the risk identification request; determining, by the client device, service indicator data associated with the service data; analyzing, by the client device, one or more of the service data and the service indicator based on a risk identification rule or a risk identification model to produce a risk result; and determining, by the client device, whether the requested service operation is a high risk operation based at least in part on the risk result.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a scan-to-pay method are provided. One of the methods includes: receiving a payment request from an operator of a mobile device; and generating a payment code based on the payment request, wherein the payment code comprises first information and second information, with the first information associated with an payment account, and the second information associated with at least one recent behavioral biometric signature of the operator and at least one historical behavioral biometric signature recorded in the mobile device. This scan-to-pay method provides robust risk control with substantially reduced cost, therefore it provides a more friendly user experience on a scan-to-pay application over its conventional counterparts.

Abstract: The present application discloses techniques for processing service requests based on risk. One example method includes: receiving a service processing request including service data; performing risk identification on the service processing request based on a stored risk identification rule or a stored risk identification model with reference to the service data to generate a risk identification result; determining that the risk identification result is an indefinite result; and in response to determining that the risk identification result is the indefinite result, sending a risk identification request that comprises the service data to a cloud risk identification system, wherein the risk identification request is configured to request the cloud risk identification system to perform risk identification on the service processing request.

Abstract: The present application discloses example methods, computer-readable mediums, and systems for controlling service operation risks. In one example, method, an application program on an end-user device monitors a service operation initiated by a user for invoking offline service information. After the service operation is monitored, it is determined whether the service operation is a risky operation based on recorded historical operation data and at least one of a predetermined risk evaluation rule or a risk evaluation model. In response to determining that the service operation is a risky operation, a refusal to invoke the offline service information is performed. In response to determining that the service operation is not a risky operation, the offline service information is invoked.

Abstract: This specification discloses techniques for risk identification. One example method includes receiving, by a client device, a risk identification request identifying a requested service operation and service data associated with the requested service operation; retrieving, by the client device, service data corresponding to the risk identification request; determining, by the client device, service indicator data associated with the service data; analyzing, by the client device, one or more of the service data and the service indicator based on a risk identification rule or a risk identification model to produce a risk result; and determining, by the client device, whether the requested service operation is a high risk operation based at least in part on the risk result.

Abstract: Implementations of the present specification disclose a method and an apparatus for detecting model security and an electronic device. The method includes the following: obtaining result data computed by using a model, wherein the result data comprises intermediate result data and output result data; obtaining a discriminator through training by using a generative adversarial network (GAN) framework, the model, and a sample; discriminating the result data by using the discriminator by using the model for current input data, to detect whether the model is currently secure, wherein the model is in a trusted execution environment for obtaining the discriminator through training; and determining a security detection result of the model.

Abstract: A rule operation request associated with a service is received by a terminal. A rule corresponding to the rule operation request is obtained from a rule set associated with the service, where the rule set has been previously obtained from the server based on at least one of a device identifier or a user identifier corresponding to the terminal. A rule tree is generated based on the rule. An operation result of the rule is determined based on the rule tree and service data related to the rule.

Abstract: The present application discloses example methods, computer-readable mediums, and systems for controlling service operation risks. In one example, method, an application program on an end-user device monitors a service operation initiated by a user for invoking offline service information. After the service operation is monitored, it is determined whether the service operation is a risky operation based on recorded historical operation data and at least one of a predetermined risk evaluation rule or a risk evaluation model. In response to determining that the service operation is a risky operation, a refusal to invoke the offline service information is performed. In response to determining that the service operation is not a risky operation, the offline service information is invoked.

Abstract: Implementations of the present specification disclose a method and an apparatus for detecting model security and an electronic device. The method includes the following: obtaining result data computed by using a model, wherein the result data comprises intermediate result data and output result data; obtaining a discriminator through training by using a generative adversarial network (GAN) framework, the model, and a sample; discriminating the result data by using the discriminator by using the model for current input data, to detect whether the model is currently secure, wherein the model is in a trusted execution environment for obtaining the discriminator through training; and determining a security detection result of the model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a scan-to-pay method are provided. One of the methods includes: receiving a payment request from an operator of a mobile device; and generating a payment code based on the payment request, wherein the payment code comprises first information and second information, with the first information associated with an payment account, and the second information associated with at least one recent behavioral biometric signature of the operator and at least one historical behavioral biometric signature recorded in the mobile device. This scan-to-pay method provides robust risk control with substantially reduced cost, therefore it provides a more friendly user experience on a scan-to-pay application over its conventional counterparts.

Abstract: Extracting characteristic information includes receiving a collection command from a client, obtaining, via a collection device, biometric information based on the collection command, selecting a stored extraction algorithm corresponding to the client, the stored extraction algorithm being selected from among a plurality of stored extraction algorithms, extracting characteristic values from the obtained biometric information, the characteristic values being extracted based on the selected extraction algorithm, and sending the extracted characteristic values to the client.

Abstract: This specification discloses techniques for risk identification. One example method includes receiving, by a client device, a risk identification request identifying a requested service operation and service data associated with the requested service operation; retrieving, by the client device, service data corresponding to the risk identification request; determining, by the client device, service indicator data associated with the service data; analyzing, by the client device, one or more of the service data and the service indicator based on a risk identification rule or a risk identification model to produce a risk result; and determining, by the client device, whether the requested service operation is a high risk operation based at least in part on the risk result.

Abstract: The present application discloses example methods, computer-readable mediums, and systems for controlling service operation risks. In one example, method, an application program on an end-user device monitors a service operation initiated by a user for invoking offline service information. After the service operation is monitored, it is determined whether the service operation is a risky operation based on recorded historical operation data and at least one of a predetermined risk evaluation rule or a risk evaluation model. In response to determining that the service operation is a risky operation, a refusal to invoke the offline service information is performed. In response to determining that the service operation is not a risky operation, the offline service information is invoked.

Abstract: The present application discloses techniques for processing service requests based on risk. One example method includes: receiving a service processing request including service data; performing risk identification on the service processing request based on a stored risk identification rule or a stored risk identification model with reference to the service data to generate a risk identification result; determining that the risk identification result is an indefinite result; and in response to determining that the risk identification result is the indefinite result, sending a risk identification request that comprises the service data to a cloud risk identification system, wherein the risk identification request is configured to request the cloud risk identification system to perform risk identification on the service processing request.

Abstract: A rule operation request associated with a service is received by a terminal. A rule corresponding to the rule operation request is obtained from a rule set associated with the service, where the rule set has been previously obtained from the server based on at least one of a device identifier or a user identifier corresponding to the terminal. A rule tree is generated based on the rule. An operation result of the rule is determined based on the rule tree and service data related to the rule.

Abstract: Embodiments of the present application disclose a method for providing a terminal identifier to a terminal. During operation, a security server receives a registration information set from the terminal, in which the registration information set includes multiple pieces of equipment information from the terminal. The security server then generates a terminal identifier based on the multiple pieces of equipment information in the registration information set. The security server then returns the terminal identifier to the terminal.

Abstract: An authentication factor is received, including an authentication key, an account information of a user, and a dynamic time factor. A bound authentication information is generated by using the authentication factor and a device information of a client device that requested the secure offline payment. The bound authentication information is transmitted to a service server system perform an offline payment authorization based on the bound authentication information. In response to a successful offline payment authorization, a graphical identifier is generated for completing the secure offline payment associated with the authentication factor, where the graphical identifier includes the bound authentication information and a dynamic password generated based on the dynamic time factor.

Abstract: Embodiments of the present application disclose a method for providing a terminal identifier to a terminal. During operation, a security server receives a registration information set from the terminal, in which the registration information set includes multiple pieces of equipment information from the terminal. The security server then generates a terminal identifier based on the multiple pieces of equipment information in the registration information set. The security server then returns the terminal identifier to the terminal.