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The Privacy Protection of Big Data Systems
Today, it seems that most people enjoy the convenience of big data from different aspects. However, while it brings convenience, danger also comes quietly. Facebook leaked 50 million users’ data.
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With the rapid development of Internet technology, many services and products are built around user data (privacy). Although this brings personalized services and improves the quality of services, our personal data is inevitably exposed in the process of data collection and used inadvertently and passively by businesses and individuals. Many researchers have begun to focus on privacy-preserving data mining (PPDM) technology in recent years.
Privacy-preserving data mining (PPDM)
- It is data mining based on privacy protection
- The core concept — By modifying the data in order to effectively execute the data mining algorithm without compromising the security of the private information contained in the data
- It is divided into 2 parts: data mining and privacy protection
Data Science
- It is a discipline that uses data to discover and solve problems
- In order to obtain effective knowledge from data, It goes through 4 steps
- Data preprocessing
- Data transformation
- Data mining
- Pattern Evaluation & knowledge presentation
Data preprocessing
- Data filtering — filtering relevant information from the database
- Data cleaning — Remove noise and inconsistent information in data, deal with missing values
- Data integration — Integrate data from disparate data sources, keep normalization and deduplication
