Objective Hair is an essential skin appendage, primarily composed of keratins and keratin-associated proteins. The protein composition and proportion of hair samples vary among different races and sexes. Currently, there is a lack of efficient methods to extract hair proteins. This study aims to explore the application of quantitative hair proteomics in distinguishing individual hair characteristics.Methods Based on the exploration of sample processing and lysis buffer using three hair samples, we developed a stable and efficient hair protein extraction method, named PLEE (PTM lab for protein extraction from hair with high efficiency). We used the PLEE method to extract seven human hair samples and performed proteomic experiments on them using in-gel digestion method to produce data for analyzing hair protein composition and proportion among individuals.Results A total of 274 proteins were identified, among which 107 proteins were commonly present, and the number of non-common proteins ranged from 57-119, with some samples having unique identification proteins. Using the 107 commonly identified proteins for quantitative protein fractionation analysis, various samples were distinguished by clustering and principal component analysis, and technical repeated samples were merged, indicating the stability of the process. In addition, 10 key proteins (KRT33A, KRTAP9-6, KRT83, KRTAP7-1, KRT32, BLMH, KRT38, KRTAP11-1, NPAS1, KRTAP4-3) with large differences between individuals and stable protein identification within the same individual were screened.Conclusion The protein composition of hair varies among different individuals, and the 10 selected proteins are expected to be key proteins for distinguishing individual hair characteristics and have significant potential applications in individual identification and criminal investigation.