Data Mining is the field of extracting and analyzing the data from large datasets. Exchange of databases is very important to get financial benefits now a day. To review business strategies and to get maximum benefit data analytics is needed. Data stored at distributed sites are integrated and published by data publisher. Data Publishing is the technique in which the data is released to others for the use. In addition to privacy preserving data size and security is also a challenge while publishing and transmitting the database. So there is a requirement of a technique which can reduce the size of database efficiently and transfer it in a secure manner. This paper proposes an efficient model for secure data publishing by using both compression and color encryption thus introducing a new approach. A new algorithm is designed and a tool is developed for implementing the proposed work.
Gaurav Kumar Ameta : is a Research Scholar, Department of Computer Science and Engineering at Sir Padampat Singhania University, Udaipur, India. His area of specialization is Data Mining, Computer Graphics, Cryptography, and Privacy Preservation.
Divya Bhatnagar : is working as Professor in the department of Computer Science and Engineering in School of Engineering, Sir Padampat Singhania University, Udaipur, India. She holds 18 years of teaching and research experience. Her specialization areas include data mining and Neural Networks.
Data Publishing, Data Mining. Distributed Databases, Tool for Data Publishing
In this paper a Tool was developed to encrypt the transactional databases. Technique used is efficient because the database is compressed to another encrypted form with compression but without losing the accuracy of database. Accuracy, security and size of database are major concerns while publishing the data. Secure data publishing is achieved without any loss of accuracy. The information of Hex Code matrix is compressed in such a manner that it becomes more compressed and secure. Such a technique is beneficial when the size of database is very large.
In future, few more security levels can be added. Overheads and related challenges are to be discussed in detail as an extension to the proposed work.
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