安全高效的云服务器回归分析外包算法

Malay Kumar, Jasraj Meena, M. Vardhan, Sanjeev Jain
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引用次数: 0

摘要

IT行业多年来一直在体验外包的好处,因为外包可以降低资本和运营支出。类似地,云计算通过互联网为客户按需提供存储、计算和其他专业服务,成本非常高。但是,将数据和计算外包给第三方云服务器会引起客户的极大担忧,因为客户会在物理上失去对其敏感/分类数据和计算的控制。失去对数据和计算的物理控制是客户使用云计算服务时感到不安全的主要问题。解决外包问题的解决方案,首先,云服务提供商必须诚实地提供正确、安全的计算;第二,外包的数据和计算在保密性和完整性方面对客户是可验证的。本文研究了回归分析、外包问题,设计了一种安全高效的外包算法,为输入提供安全保障,同时也为在云服务器上计算的输出结果提供保障。此外,还开发了一种新颖有效的结果验证技术,以最优概率为1来检测服务器不当行为和作弊。并与现有算法进行了理论分析和实验分析,验证了所提算法的高效性、安全性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure and Efficient Regression Analysis Outsourcing Algorithm for Cloud Server
IT industry has been experiencing the benefits of outsourcing for years, since the outsourcing brings down both the capital and operational expenditure. Similarly, cloud computing provides storage, computation, and other specialized services on demand to customers over the internet at a very generous cost. However, outsourcing data and computation to a third party cloud server is a great cause of concern to the client because a customer physically loses control over their sensitive/classified data and computation. The loss of physical control over the data and computation is the main issue for a client that makes him feel insecure using cloud computing services. The solution to address outsourcing issues, first, the cloud service provider must be honest by providing correct and secure computation; second, the outsourced data and computation shall be verifiable to customers in terms of confidentiality and integrity. In this paper, we investigate the problem of regression analysis, outsourcing problem and devise a secure and efficient outsourcing algorithm which provides security for the input and also provide safeguards to the output result computed on cloud servers. Further, a novel and efficient result verification technique have been developed to detect server misbehavior and cheating with optimal probability of 1. Furthermore, theoretical and experimental analysis has compared with existing algorithm to demonstrate the efficiency, security and effectiveness of the proposed algorithms.
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