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Résumé : Differential privacy (DP) is a widely accepted statistical framework for protecting data privacy. The idea of DP was initially introduced to human private data, mainly medical and health records, but it is now clear that the same ideas can have a major contribution in infrastructure systems, including railway track engineering. This chapter introduces the concept of differential privacy to railway track data collection and evaluation. DP is the current application that is discussed in the realm of sensitivity of railway track data and in addressing how the sensitivity attributes in track data can cause unwarranted danger to the safety and smooth operation of the train, for example, how an intruder to railway track monitoring data could be capable of identifying some of the critical and vulnerable parts of the track. There are three kinds of privacy protections: data collection protection, data releasing protection, and data analysis protection.