De privacy encryption and extraction model of smart grid data based on Spark Streaming

Abstract

In order to ensure the safe and efficient application of smart grid data, this paper studies the de privacy encryption and extraction of smart grid data based on Spark Streaming, and accurately completes the de privacy encryption and extraction of smart grid data. The construction of the model mainly includes two parts, which are de privacy decryption processing and data extraction. After data privacy is processed by using collaborative cognitive model, the data is processed by Spark Streaming, including data cleaning, data reduction, data standardization, etc. Then the data clustering center is extracted by using genetic neural algorithm. Finally, the similarity between the data set and the clustering center is calculated, and the data with the greatest similarity is selected to realize data extraction. The test results show that: the model can quickly complete data cleaning, effectively identify the abnormal data information in the data, the recognition rate is 99.72%, and complete data clustering in a few iterations, so as to realize the de privacy encryption and extraction of smart grid data.