A Survey on Privacy Preserving Data Mining Techniques

Enormous amount of detailed private data is recurrently collected and analysed by applications using data mining, sharing of these data is useful to the application users. While sharing the private data, privacy preserving is becoming an increasingly significant issue. Sequential pattern mining is the process of finding relevant pattern in the data set. Sequential pattern helps in envisaging the next event. Predicting the sequence datasets leads to violate the privacy and disclose sensitive patterns related to medical records, business secrets etc.This paper explores about different various techniques for privacy preserving data mining such as anonymity, randomization, secure multiparty computation, sequential pattern hiding.