Accomplishing Data Integrity and Confidentiality in Data Markets
Srinivasa Bapiraju Gadiraju1, Devi Priya Gottumukkala2, Sree Vidya Dandu3, Naga Mallik Atcha4, Priyanka Vemulavada5
1Dr. Srinivasa Bapiraju Gadiraju, Professor, Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Affiliated to JNTUH, Hyderabad. India.
2Devi Priya Gottumukkala, Assistant Professor, Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Affiliated to JNTUH, Hyderabad. India.
3Sree Vidya Dandu, Assistant Professor, Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Affiliated to JNTUH, Hyderabad. India.
4Naga Mallik Atcha, Assistant Professor, Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Affiliated to JNTUH, Hyderabad. India.
5Priyanka Vemulavada, PG Scholor, M.Tech, Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Affiliated to JNTUH, Hyderabad. India.
Manuscript received on 06 September 2019. | Revised Manuscript received on 22 September 2019. | Manuscript published on 30 September 2019. | PP: 49-52 | Volume-8 Issue-11, September 2019. | Retrieval Number: J99240881019/2019©BEIESP | DOI: 10.35940/ijitee.J9924.0981119
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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: As a noteworthy business worldview, a few on-line information stages have developed to fulfill society’s wants for individual explicit learning, any place a service provider assembles raw data from data givers, at that point offers data services to data clients. Notwithstanding, inside the data exchanging level, the data customers face a squeezing issue, i.e., an approach to confirm whether the service provider has actually gathered and handled data. During this paper, we propose TPDM, that effectively compose truthfulness and Privacy protection in data Markets. TPDM is structured inside in partner degree Encrypt-then-Sign way; utilize mostly homomorphism encryption and identity-based signature. It along encourage bunch confirmation, processing, and result check, though giving identity protection and data confidentiality. We used dataset and 2015 RECS dataset, severally. Our examination and investigation results that TPDM accomplishes numerous alluring properties, though obtaining low calculation and correspondence overheads once sustaining huge size data markets.
Keywords: Data markets, truthfulness, privacy protection.
Scope of the Article: Marketing and Social Sciences