A Bigdata Process for Practical Privacy-Preserving Utilizing k-Means Clustering
Praveen S. Banasode1, Sunita Padamannavar2
1Praveen S. Banasode, Jain College of Engineering, Belagavi affiliated to Visvesvaraya Technological University, Belagavi Karnataka, India.
2Dr. Sunita Padamannavar, KLS Gogte Institute of Technology, Belagavi Affiliated to Visvesvaraya Technological University, Belagavi. Karnataka, India.
Manuscript received on November 02, 2019. | Revised Manuscript received on November 15, 2019. | Manuscript published on December 30, 2019. | PP: 4822-4824 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4085129219/2019©BEIESP | DOI: 10.35940/ijeat.B4085.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Now a day’s privacy preservation is the big issue on growing big data in various field such as medical, engineering and physical with the fast growing network. One of the most important challenges in handling big data is security issues. To overcome such security issues cryptographic concepts have been used in this paper to provide high security of big data’s with the low consumption of time for both encryption and decryption process. In this paper the proposed method is Indexed RSA (IRSA) which is developed with modified scheme. We offered a method to index the keyword before encrypting the file and based on the indexed keyword the search has been done. Finally the security analysis was carried out and the analysis showed that our modified scheme can meet the security requirement against brute force attack and SQL injection attack.
Keywords: IRSA, Encryption, Decryption, Big Data