System for Analyzing Crime News by Mining Live Data Streams with Preserving Data Privacy

Data stream mining is an emerging field of data science. It is a process of extraction of knowledge from streaming data using incremental algorithms. Mining streaming data comes with different challenges [3] like concept drift, handling incomplete and delayed information, skewness of data, and privacy preservation. Privacy of streaming data should be maintained during the process of its mining and processing to protect sensitive information from attackers and also to preserve user-sensitive personal data that is vulnerable to malicious purposes. In this paper, we proposed a system for mining crime news data streams along with privacy preservation of sensitive data using K-anonymization and Apache Spark. The knowledge gained through the process of mining streaming data is visualized in the form of real-time updating charts which provides the end-user with useful insights about current crime rates and statistics in the popular cities of India.