Security vulnerability and encryption technology of computer information technology data under big data environment

Abstract

In recent years, the traditional encryption storage technology and management methods have been difficult to satisfy the demand of big data in terms of speed, capacity, storage efficiency and security, along with the rapid increase of data volume. Data security is facing great challenges and challenges. To solve this problem, this paper proposes a de-redundancy method based big data encryption algorithm. Firstly, bloom filter technology is used to decrease the dimension of big data. Based on its remarkable advantages, bloom filter space and query efficiency and variable-length block detection scheme with less additional overhead, duplicate data detection and deletion algorithm suitable for large data is designed and implemented. Secondly, based on eliminating redundancy of big data, combined with the characteristics of the elliptic curve encryption algorithm and AES block cipher mode in terms of computing speed, parallelism and security, an encryption approach based on data de-redundancy technology is presented. According to the evaluation system of the encryption algorithm, the encryption time, keyspace and security of the new algorithm are evaluated. Experimental results reveal that the scheme has better security, and the presented approach can increase the speed of the encryption process, and decrease the encryption time and consumption.