Biblio

Aiming at the poor stability of traditional communication data encryption methods, a point-to-point encryption method of power system communication data based on block chain technology is studied and designed. According to the principle of asymmetric key encryption, the design method makes use of the decentralization and consensus mechanism of block chain technology to develop the public key distribution scheme. After the public key distribution is completed, the sender and receiver of communication data generate the transfer key and pair the key with the public key to realize the pairing between data points. Xor and modular exponentiation are performed on the communication data content, and prime Numbers are used to fill the content data block. The receiver decrypts the data according to the encryption identifier of the data content, and completes the design of the encryption method of communication data point to ground. Through the comparison with the traditional encryption method, it is proved that the larger the amount of encrypted data is, the more secure the communication data can be, and the stability performance is better than the traditional encryption method.

Hadoop is developed as a distributed data processing platform for analyzing big data. Enterprises can analyze big data containing users' sensitive information by using Hadoop and utilize them for their marketing. Therefore, researches on data encryption have been widely done to protect the leakage of sensitive data stored in Hadoop. However, the existing researches support only the AES international standard data encryption algorithm. Meanwhile, the Korean government selected ARIA algorithm as a standard data encryption scheme for domestic usages. In this paper, we propose a HDFS data encryption scheme which supports both ARIA and AES algorithms on Hadoop. First, the proposed scheme provides a HDFS block-splitting component that performs ARIA/AES encryption and decryption under the Hadoop distributed computing environment. Second, the proposed scheme provides a variable-length data processing component that can perform encryption and decryption by adding dummy data, in case when the last data block does not contains 128-bit data. Finally, we show from performance analysis that our proposed scheme is efficient for various applications, such as word counting, sorting, k-Means, and hierarchical clustering.

In the existing remote data integrity checking schemes, dynamic update operates on block level, which usually restricts the location of the data inserted in a file due to the fixed size of a data block. In this paper, we propose a remote data integrity checking scheme with fine-grained update for big data storage. The proposed scheme achieves basic operations of insertion, modification, deletion on line level at any location in a file by designing a mapping relationship between line level update and block level update. Scheme analysis shows that the proposed scheme supports public verification and privacy preservation. Meanwhile, it performs data integrity checking with low computation and communication cost.