Research Paper on M-Privacy For Collaborative Data Publishing
In recent years, privacy takes an important role to secure the data from various probable attackers. When data
need to be shared for public advantage as required for Health care and researches, individual privacy is major concern
regarding sensitive information. So while publishing such data, privacy should be conserved. While publishing collaborative
data to multiple data provider’s two types of problem occurs, first is outsider attack and second is insider attack. Outsider
attack is by the people who are not data providers and insider attack is by colluding data provider who may use their own
data records to understand the data records shared by other data providers. This problem can be overcome by combining
slicing techniques with m-privacy techniques and addition of protocols as secure multiparty computation and trusted third
party will increase the privacy of system effectively.
Index Terms— Privacy, Security, Integrity, and Protection, Distributed Databases.