Secure Sum Computation using Threshold Encryption for Semi-Ideal Model
Rashid Sheikh1, Durgesh Kumar Mishra2
1Rashid Sheikh, Computer Science and Engineering Department, Mewar University, Chittorgarh, India.
2Durgesh Kumar Mishra, Computer Science and Engineering Department, Sri Aurobindo Institute of Technology, Indore, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4406-4409 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6563018520/2020©BEIESP | DOI: 10.35940/ijrte.E6563.018520
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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: The need of preserving privacy of data arises when multiple parties work together on some common task. In this scenario each of the parties has to provide its sensitive data for a common function evaluation. But, the parties may be worried about the misuse of the data. Here comes the subject of Secure Multiparty Computation (SMC). The area where multiple cooperating parties jointly evaluate a common function of their data while preserving the privacy and getting the correct result is SMC. Here, we devise a new model and algorithm to compute sum of private data of mutually distrustful cooperating parties. We coin the term Semi-Ideal Model as it is hybrid of Ideal model and real model. The computation is secure on insecure network as well.
Keywords: Secure Multiparty Computation, Secure Sum, Semi-Honest Model, Trusted Third Party.
Scope of the Article: Computational Economics, Digital Photogrammetric.