Large file selective encryption method for reducing write

Abstract

The invention belongs to the field of information security, relating to a large file encryption method. The method considers the phenomenon that a large file has huge data and is not suitable for full encryption, a large number of data will choose not to be encrypted, and in order to reduce the read and write of the data, especially the write, the method disclosed by the invention adopts the following steps: storing an original plaintext, covering part of the plaintext that is encrypted, and separately storing an encrypted ciphertext. As different encryption methods have different advantages and disadvantages, fully homomorphic encryption also cannot solve all delegated calculations, and a high cost of encryption is needed, an encryption mode with a misleading function is required for some data, and only a general symmetric encryption mode is required for other data, thereby, the appropriate encryption methods are segmentally selected as required, only part of the data needs to be encrypted according to rules or selections; and meanwhile, an optimum scheme for reducing key management and guaranteeing security is proposed, and thus the encryption and decryption of the files can be achieved by only using fewer keys.

Description

technical field [0001] The invention belongs to the field of information security and relates to a method for selectively encrypting large files. Background technique [0002] With the development of information technology, some files are getting bigger and bigger. At present, some files of very popular big data (big data, mega data) are also very large. Taking Hadoop as an example, there are many file formats in Hadoop, and the more representative one is SequenceFile (and its similar file types) : SequenceFile is a binary file provided by Hadoop API, which serializes data into files in the form of <key, value>. This binary file internally uses Hadoop's standard Writable interface to implement serialization and deserialization. It is representative of the file format in the big data environment and is compatible with MapFile in the Hadoop API. Some big data files are stored in real time, such as video. After the file is recorded and stored, it may be found that some...

AI Technical Summary

Problems solved by technology

Some big data files are stored in real time, such as video. After the file is recorded and stored, it may be found that some data needs to be kept confidential and needs to be encrypted. However, it is obviously unrealistic to encrypt a large amount of data.

For the encryption of cloud computing and big data, there are currently proxy re-encryption and homomorphic encryption. These encryptions have certain applications and limitations. For example, homomorphic encryption has low efficiency and high redundancy. Larger limitations, the above-mentioned encryption method is unrealistic to be used directly to encrypt large-scale data, because the amount of calculation is huge, and such as homomorphic encryption often brings data expansion, the cost is high, heavy proxy encryption is only suitable for Key conversion between specific users. In reality, it is not necessary to encrypt all data as described above

Homomorphic encryption is more suitable for the encryption of data that needs to be calculated, but the cost is relatively high

Encrypting these data with traditional encryption methods also has problems such as large amount of calculation