An identity recognition method, comprising: collecting big data of address books, the big data of address books comprising address books of multiple users, each address book comprising multiple identity information pairs, and each identity information pair comprising a name and a mobile phone number; performing statistical analysis on the identity information pairs in the big data of address books to obtain an information weight corresponding to each of the identity information pairs, the information weight indicating a degree of credibility of the identity information pair; obtaining an information weight corresponding to the identity information pair of a user to be recognized from the statistical analysis result; and if the obtained information weight satisfies a risk condition , determining that the user to be recognized is a user having a risk, characterized in that : performing said statistical analysis comprises calculating a pagerank value of each of the identity information pairs using a pagerank method, and using the pagerank value as the information weight of the identity information pair, wherein each identity information pair is a node in a graph model, an outbound link of a node points to another identity information pair in the address book of the user to which the identity information pair belongs, and an inbound link of a node comes from an identity information pair of a user in an address book comprising the identity information pair corresponding to the node. collecting big data of address books, the big data of address books comprising address books of multiple users, each address book comprising multiple identity information pairs, and each identity information pair comprising a name and a mobile phone number; performing statistical analysis on the identity information pairs in the big data of address books to obtain an information weight corresponding to each of the identity information pairs, the information weight indicating a degree of credibility of the identity information pair; obtaining an information weight corresponding to the identity information pair of a user to be recognized from the statistical analysis result; and if the obtained information weight satisfies a risk condition , determining that the user to be recognized is a user having a risk, characterized in that : performing said statistical analysis comprises calculating a pagerank value of each of the identity information pairs using a pagerank method, and using the pagerank value as the information weight of the identity information pair, wherein each identity information pair is a node in a graph model, an outbound link of a node points to another identity information pair in the address book of the user to which the identity information pair belongs, and an inbound link of a node comes from an identity information pair of a user in an address book comprising the identity information pair corresponding to the node. performing said statistical analysis comprises calculating a pagerank value of each of the identity information pairs using a pagerank method, and using the pagerank value as the information weight of the identity information pair, wherein each identity information pair is a node in a graph model, an outbound link of a node points to another identity information pair in the address book of the user to which the identity information pair belongs, and an inbound link of a node comes from an identity information pair of a user in an address book comprising the identity information pair corresponding to the node. <EOS>