Special Issue Article Open Access

Preserve Privacy Data Using Stile Methods

Abstract

Preserve privacy data using sTile methods addresses the challenge of executing computations on untrusted machines in a trustworthy manner. Its focus is on preserving data privacy while solving computationally intensive problems on untrusted machines. Existing work presented sTile technique for building software systems that distribute large computations onto the cloud while providing guarantees that the cloud nodes cannot learn the computation’s private data. sTile is based on a nature-inspired, theoretical model of self-assembly. In this paper, we present a prototype implementation that solves NP-complete problems. sTile explores the fundamental cost of privacy through data distribution. Tile assemblies are Turning universal, so future extensions of sTile can be made to perform arbitrary computations and to automatically compile programs into tile assemblies.

P.Nithya and M.Lakshmi prabha

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