Proposed Approach to Sensitive Association Rules Protection based on Compressing and Cryptography: (SARP-CC)

摘要

Privacy-preserving data mining is a modern technology that has been studied by many researchers. There are two types of Privacy-preserving association rules regarding the type of sensitive dataset to be protected, either protect the raw data before performing the data mining process or protect the sensitive knowledge extracted after performing the data mining process. In this research, we will suggest a technique called (SARP-CC) for privacy-preserving data mining. It will be used to protect sensitive knowledge (sensitive association rules) by changing the representation of knowledge from its known form to another, where it is more compressed and encrypted so that it can be sent over a network. The results show that this new compressed and encrypted form reduces storage space and transmission time and facilitates the transmission process over the network, and very beneficial especially for insecure networks. It can also be used as part of secure distributed association rules mining algorithms.