Simulation of Unsupervised Encryption Method for Big Data in Mobile Network Base Station
To ensure data integrity and reliability,it is necessary to collect and store data for many times,which increases data redundancy and difficulty in encrypting base station data.In order to solve this problem,an unsuper-vised encryption method for big data of mobile network base stations was presented.Firstly,an unsupervised redun-dancy elimination algorithm was designed.For the same data,variable-sized partition method was used to identify and delete duplicate data.For similar data,Bloom filter was used to identify and delete similar data,thus reducing data re-dundancy.Logistic mapping was combined with Henon mapping to form a double chaotic sequence as the encryption key of Advanced Encryption Standard(AES)algorithm.Finally,the unsupervised encryption of big data in mobile net-work base station was achieved.The experimental results show that the time delay of encryption and decryption of the proposed method is less than 12ms,and the throughput is high.
Big data of Mobile base stationUnsupervisedAnti-crackingData redundancy reductionChaotic en-cryption
万方数据
维普
