Feature Extraction and Feature Selection : Reducing Data Complexity with Apache Spark

Dimitrios Sisiaridis, Olivier Markowitch
2017 International journal of network security and its applications  
Feature extraction and feature selection are the first tasks in pre-processing of input logs in order to detect cyber security threats and attacks while utilizing machine learning. When it comes to the analysis of heterogeneous data derived from different sources, these tasks are found to be time-consuming and difficult to be managed efficiently. In this paper, we present an approach for handling feature extraction and feature selection for security analytics of heterogeneous data derived from
more » ... ifferent network sensors. The approach is implemented in Apache Spark, using its python API, named pyspark.
doi:10.5121/ijnsa.2017.9604 fatcat:gell6jwlkvbvfcqfgyoghdolvu