Big Data Privacy using Fully Homomorphic Non-deterministic Encryption

被引：0

作者：

Patil, Tejashree B. ^{[1
]}

Patnaik, Girish Kumar ^{[1
]}

Bhole, Ashish T. ^{[1
]}

机构：

[1] North Maharashtra Univ, SSBTs Coll Engn & Technol, Dept Comp Engn, Jalgaon, Maharashtra, India

来源：

2017 7TH IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC) | 2017年

关键词：

Security and Privacy; Big Data; Encryption; Non-deterministic; Fully homomorphic encryption;

D O I：

10.1109/IACC.2017.33

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Big data is a large amount of digital information. Now days, data security is a challenging issue that touches several areas along with computers and communication. The security of data which stored online has become a main concern. Several attackers play with confidentiality of the user. Cryptography is a approach that provide data security to the user. Despite of huge efforts to protect sensitive data, hackers typically manage to steal it. Computing with encrypted data is strategies for safeguarding confidential data. The partial homomorphic encryption is specialized for only one operation on the encrypted data. For example the Pailliers encryption scheme performs only one mathematical operation on encrypted numerical data and is successful to compute the sum of encrypted values. The Pailliers encryption scheme is unable to do multiple mathematical operations on encrypted numerical data. The proposed encryption algorithm computes more than one mathematical operation on encrypted numerical data thereby further protecting the encrypted sensitive information.

引用

页码：138 / 143

页数：6