Nirali R. Nanavati

Learn More
The current massive proliferation of data has led to collaborative data mining that requires preservation of individual privacy of the participants. A number of algorithms proposed till date in this scenario are limited to mining association rules and do not consider their cyclic nature that finds associations with respect to the time segment. Hence(More)
Collaborative data mining has become very useful today with the immense increase in the amount of data collected and the increase in competition. This in turn increases the need to preserve the participants' privacy. There have been a number of approaches proposed that use Secret Sharing for privacy preservation for Secure Multiparty Computation (SMC) in(More)
Privacy preservation while undertaking collaborative data mining is a significant research problem. The vertically partitioned data model is an important data partition model and has varied applications. The vertically partitioned data model necessitates a non-collusive scheme and an efficient scheme for the problem of privacy-preserving distributed(More)
Association Rule Mining (ARM), a Data Mining process, extracts hidden strong relationships among a large set of the correlated data. With the burgeoning advancement and application of Association Rule Mining in diverse fields ranging from the web usage mining to medical diagnosis and business intelligence to geographical information systems, the(More)
  • 1