Abstract: A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions.

Abstract: A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions.

Abstract: A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions.

Abstract: A method of identifying risky user behaviors in computer networks includes determining behavior data of a user. The behavior data describes user activities of the user using a computer network. A particular event chain is identified from the behavior data. The particular event chain includes one or more events of the user activities. A risk coefficient of the particular event chain is determined. Based on the risk coefficient, whether the particular event chain represents a risky user behavior is determined.

Abstract: A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions.

Abstract: A method of user identity verification by a server, where the server pre-configures, by use of collected user information, verification information corresponding to accounts of users in a user verification information data store, the verification information including a plurality of verification security challenges and a plurality of respective first verification answers. The method includes detecting a condition to whether initiate a user identity verification is satisfied, where an account ID of a user is obtained from the condition. The method also includes inquiring the pre-configured user verification information about verification information matching the account ID and transmitting security challenges of the inquired verification information to the client.

Abstract: A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions.

Abstract: A method of identifying risky user behaviors in computer networks includes determining behavior data of a user. The behavior data describes user activities of the user using a computer network. A particular event chain is identified from the behavior data. The particular event chain includes one or more events of the user activities. A risk coefficient of the particular event chain is determined. Based on the risk coefficient, whether the particular event chain represents a risky user behavior is determined.

Abstract: A method of user identity verification by a server, where the server pre-configures, by use of collected user information, verification information corresponding to accounts of users in a user verification information data store, the verification information including a plurality of verification security challenges and a plurality of respective first verification answers. The method includes detecting a condition to whether initiate a user identity verification is satisfied, where an account ID of a user is obtained from the condition. The method also includes inquiring the pre-configured user verification information about verification information matching the account ID and transmitting security challenges of the inquired verification information to the client.

Abstract: A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions.