基于改进属性加密的多源大数据安全访问控制
Secure Access Control for Multi-Source Big Data Based on Improved Attribute Encryption
胡燕1
作者信息
- 1. 罗定开放大学 教务处,广东 罗定 527200
- 折叠
摘要
用户在访问多源大数据的共享过程中,易被恶意用户盗取隐私数据,导致多源大数据文件的安全性较低.为此,提出基于改进属性加密的多源大数据安全访问控制方法.构建基于密文策略属性加密(CP-ABE)的多源大数据安全访问控制模型,利用属性、访问结构、访问树三部分组成CP-ABE,通过生成主密钥和私钥、加密多源大数据、生成私钥以及解密密文四个步骤控制多源大数据安全访问,并通过全面定义主密钥和公钥的生成、加密多源大数据文件、获取访问用户授权和读写该数据文件、控制访问用户权限,改进CP-ABE,将CP-ABE与多源大数据安全访问控制模型有效结合,提高多源大数据安全访问控制效果.实验结果表明,该方法产生私钥的效率较高、存储开销较低,可提高加密多源大数据的安全性,阻止恶意用户任意访问多源大数据文件,保障数据安全.
Abstract
During the sharing process of accessing multi-source big data,users are susceptible to theft of private data by malicious users,resulting in low security of multi-source big data files.Therefore,a secure ac-cess control method for multi-source big data based on improved attribute encryption is proposed.The research builds a secure access control model for multi-source big data based on ciphertext policy attribute-based encryp-tion(CP-ABE).CP-ABE is composed of attributes,access structure,and access tree.It controls the secure access of multi-source big data through four steps:generating master key and private key,encrypting multi-source big data,generating private key,and decrypting ciphertext,and comprehensively defines the generation of master key and public key,encrypting multi-source big data files Obtain access user authorization,read and write the data file,control access user permission,improve CP-ABE,effectively combine CP-ABE with multi-source big data security access control model,and improve multi-source big data security access control effect.The experimental results show that this method has high efficiency in generating private keys,low storage overhead,can improve the security of encrypting multi-source big data,prevent malicious users from arbitrarily accessing multi-source big data files,and ensure data security.
关键词
改进属性加密/多源大数据/安全访问控制/控制机制/CP-ABE算法Key words
improved attribute encryption/multi-source big data/secure access control/control mecha-nism/CP-ABE algorithm引用本文复制引用
基金项目
广东省教育厅科学研究项目(2019GKTSCX132)
出版年
2023
NETL
NSTL
维普
万方数据