The invention discloses an identity
authentication method and
system based on electroencephalogram characteristics. The method comprises the following steps: model training,
password setting,
alpha wave test, electroencephalogram characteristic extraction and classification, and model updating. The electroencephalogram characteristic extraction and classification method is composed of pre-training layer by layer, network
fine tuning and classification. According to the identity
authentication method and
system disclosed by the invention, first level
authentication is performed on a tester by means of the property that the alpha
waves fluctuate greatly when the tester is
lying, meanwhile the existing method is improved to establish a
feature extraction method based on a depth belief network, meanwhile the
feature extraction method is optimized by using an immune leapfrog
algorithm, and when the tester observes
password patterns,
feature extraction and classification are performed on the
brain waves so as to perform second level authentication. By means of the two levels of authentication, the security of the user can be guaranteed, and the improved depth belief network can also improve the existing identification precision, ensure less error rates, avoid a large number of false alarms and bring good user experience.