Aiming at the properties of the palm bio-impedance spectroscopy (PBIS) data and shortage of the existing algorithms, this paper proposed a kind of the PBIS identification method based on immune clone. This method mainly consisted of three parts, which are data normalization, feature selection and matching. The PBIS algorithm constructed a new classifier based on the immune clone selection algorithm (ICSA) and the hidden space support vector machine (HSSVM), called the ICSA-HSSVM. It was compared with other classifiers such as Euclidean distance, cosine distance and support vector machine (SVM). The experimental results show that the proposed classification method can achieve more than 95% accuracy in identity recognition. The PBIS biometric identification tech depends on the human body inherent characteristics to carry out the status identification so as to overcome the drawbacks of traditional information safety tech status identification. The main advantages of PBIS algorithm include four aspects. The first is the uniqueness, universality, stability, easy collection, and it is basically not being subject to the influence of pathological changes in the human body positions. The second is not sensitive to the environment and the excellent recognition performance can be obtained through the method easily. The three is high stability and uniqueness when it is served as the biometric potentiality, being in agreement with biometric identification requirements. (4) The four is able to resist against counterfeiting attacks effectively. The method proposed in this paper is of great theoretical and practical values in the fields of national public security, internet information security, military communication security, micro-blog micro-message public opinion supervision.