A file reputation acquiring method, comprising: acquiring at least one function in the accessed file and acquiring a function hash value of each function in the at least one function to obtain at least one function hash value, wherein the accessed file is an executable program file, and each function is a segment of instruction data; determining, by using a classifier obtained in advance by training, a probability distribution separately corresponding to each function hash value in the at least one function hash value, wherein the probability distribution is used to indicate a probability that each function hash value appears in a file of a black sample set, and a probability that each function hash value appears in a file of a white sample set, wherein the black sample set comprises at least one malicious program file, and the white sample set comprises at least one normal program file; and determining a reputation value of the accessed file according to the probability distribution corresponding to each function hash value; wherein the determining a reputation value of the accessed file according to the probability distribution corresponding to each function hash value comprises: determining whether a function hash value, whose probability distribution indicates that a probability that the function hash value appears in the file of the black sample set is higher than a first preset threshold, exists in the accessed file; determining whether a quantity of function hash values, whose probability distributions indicate that probabilities that the function hash values appear in the file of the black sample set are higher than the first preset threshold, exceeds a preset quantity; and if function hash values, whose quantity exceeds the preset quantity and whose probability distributions indicate that probabilities that the function hash values appear in the file of the black sample set are higher than the first preset threshold, exist, determining that the accessed file has a reputation value lower than a second preset threshold. acquiring at least one function in the accessed file and acquiring a function hash value of each function in the at least one function to obtain at least one function hash value, wherein the accessed file is an executable program file, and each function is a segment of instruction data; determining, by using a classifier obtained in advance by training, a probability distribution separately corresponding to each function hash value in the at least one function hash value, wherein the probability distribution is used to indicate a probability that each function hash value appears in a file of a black sample set, and a probability that each function hash value appears in a file of a white sample set, wherein the black sample set comprises at least one malicious program file, and the white sample set comprises at least one normal program file; and determining a reputation value of the accessed file according to the probability distribution corresponding to each function hash value; wherein the determining a reputation value of the accessed file according to the probability distribution corresponding to each function hash value comprises: determining whether a function hash value, whose probability distribution indicates that a probability that the function hash value appears in the file of the black sample set is higher than a first preset threshold, exists in the accessed file; determining whether a quantity of function hash values, whose probability distributions indicate that probabilities that the function hash values appear in the file of the black sample set are higher than the first preset threshold, exceeds a preset quantity; and if function hash values, whose quantity exceeds the preset quantity and whose probability distributions indicate that probabilities that the function hash values appear in the file of the black sample set are higher than the first preset threshold, exist, determining that the accessed file has a reputation value lower than a second preset threshold. determining whether a function hash value, whose probability distribution indicates that a probability that the function hash value appears in the file of the black sample set is higher than a first preset threshold, exists in the accessed file; determining whether a quantity of function hash values, whose probability distributions indicate that probabilities that the function hash values appear in the file of the black sample set are higher than the first preset threshold, exceeds a preset quantity; and if function hash values, whose quantity exceeds the preset quantity and whose probability distributions indicate that probabilities that the function hash values appear in the file of the black sample set are higher than the first preset threshold, exist, determining that the accessed file has a reputation value lower than a second preset threshold.