Abstract: To establish a rapid method for inspecting packaging paper and provide assistance to the work of public security organs,non-destructive testing was conducted on 76 different brands of packaging paper samples using infrared spectroscopy technology,which is easy to operate,reusable,and non-destructive.Firstly,the position of the infrared absorption peak of the sample is analyzed,and the filler contained in the sample is determined,and then the sample is manually classified according to the different filler composition,and then the samples are clustered by K-MEANS method to verify the accuracy of manual classification.Finally,based on the clustering results,a support vector machine algorithm is constructed and a identification model for packaging paper evidence is established.Randomly select 50%of the samples as the training set and 50%of the samples as the testing set.The results show that the accuracy of the testing set is 97.368%,the recall rate is 97.368%,and the accuracy rate is 97.478%.Realized rapid non-destructive identification of packaging paper.This classification model method has good operability,accurate and reliable results,and can provide assistance for public security organs in solving cases.