Virus program detection method, terminal, and computer readable storage medium

A terminal device, comprising a memory for storing a set of instructions and a processor in communication with the memory, the processor, when executing the set of instructions, is configured to:

• obtain a full characteristic features of a first file, the first file being a sample file collected by a client application of the terminal device, and the full characteristic features being used to uniquely determine all components of the first file;
• maintain reference binary hash sequences in an antivirus database, each corresponding to one type of virus-infected file;
• obtain a first binary hash sequence based on the full characteristic features of the first file and by using a preset hash algorithm;
• calculate similarity parameters between the first binary hash sequence and the reference binary hash sequences in the antivirus database;
• and
• determine the first file as a virus-infected file when at least one of the similarity parameter is less than a preset similarity threshold.

A non-transitory computer readable storage medium for storing program instructions, the program instructions, when executed by a processor of a terminal device, cause the terminal device to perform:

• obtaining a full characteristic features of a first file, the first file being a sample file collected by a client application of the terminal device, and the full characteristic features of the first file being used to uniquely determine all components of the first file;
• obtaining a first binary hash sequence based on the full characteristic features of the first file and by using a preset hash algorithm;
• calculating similarity parameters between the first binary hash sequence and multiple binary hash sequences in an antivirus database, each binary hash sequence in the antivirus database corresponding to one type of virus-infected file;
• and
• determining the first file as a virus-infected file when at least one of the similarity parameters is less than a preset similarity threshold.