Data Security And Data Privacy

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Data privacy refers to the sensitive information that individuals, organizations or other entities would not like to expose to the external world. For example, medical records can be one kind of privacy data. Privacy data usually contain sensitive information that is very important to its owner and should be processed carefully.
Data privacy is not equal to data security. Data security ensures that data or information systems are protected from invalid operations, including unauthorized access, use, exposure, damage, modification, copy, deletion and so on. Data security can’t guarantee data privacy and vice versa. Figure 1 shows the relation between data security and data privacy. A represents the situation where data privacy is violated while …show more content…

SSNs, bank accounts, medical records and so on), the violation of data privacy can cause very serious consequences like identity thefts. Therefore, privacy preservation is very necessary and important.
Obviously, the purpose of privacy preservation is to avoid the exposure of sensitive information. Moreover, a good privacy preservation method should not affect the usage and analysis of privacy data. For example, the privacy preservation method should not cause a lot of data loss or greatly affect the efficiency of data analysis. It’s important to find a balance between privacy preservation and data availability.
2.2 Big …show more content…

Although the term Big Data has been well known by people, there is no common definition of it. Among various existing definitions of big data, the one put forward by Gantz and Reinsel in 2011 is relatively more recognized. Their definition claims that big data represents very large volumes of all kinds of data [2]. Another widely recognized definition is proposed in a report of McKinsey & Company [3]. The report claims, “Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”. From these definitions, we can know that one important feature of big data is large size. However, the definition of “large size” may vary over time. In recent years, with the emergence and development of social networks (e.g. Facebook, twitter), electronic commerce (e.g. eBay, Amazon) and other network platforms, volume of data grew very fast. We used to regard gigabyte (GB) as “large size”, but nowadays only above petabyte (PB, equals to 106 GB) level can be called “large size”. Although large volume is one characteristic of big data, it doesn’t mean that big data is equivalent to massive data. There are also some other characteristics that can distinguish

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