⃞ big data security
Big data security is largely divided into infrastructure-based security, data encryption and management security, and security monitoring.
In addition, various legal issues regarding the data to be used for big data utilization, such as the Personal Information Protection Act, the Information and Communications Network Act, and the Copyright Act, are also important elements of security, and these big data security elements are independent of each other.
However, as a large factor for the utilization of big data, they are driven in connection with each other.
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| Big data security Issue |
⃞ Security issues related to big data storage.
It is how you can safely manage your data.
Recently, the range of personal information is expanding, and there are various sensitive information surrounding individuals in addition to PI (Personal Identification) that can identify individuals.
For example, location information produced by a specific individual while moving, image information taken by an individual, etc. can be classified as sensitive information, and governments and companies have confidential data such as internal information. whether you can It is one of the important elements of a big data platform.
– PPDM(Privacy Preserving Data Mining)
⃞ Big data processing security issues(NoSQL and Hadoop security)
There are two main systems for big data processing. Unlike existing database software (e.g., Oracle Database, MS SQL, etc.), it is an open-source database that is optimized for processing large amounts of data. It is a security issue for NoSQL and Hadoop security, which is the de facto standard of big data platforms.
When constructing a big data system, it is necessary to identify the individual characteristics of NoSQL and identify and respond to each vulnerability. In the case of Hadoop, HA configuration according to Name Node failure must be performed accurately.
⃞ technology security
Big data uses a combination of many technologies, search technology, etc. are used to process large amounts of data, and data management technologies that are widely used in databases are applied.
As various technologies are used, unexpected errors may occur when linking various technologies, and various vulnerabilities are discovered in terms of security.
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| Big data and information security |
⃞ data security
To utilize big data, securing data stability is a prerequisite. In order to safely utilize data, it is necessary to secure anonymity for personal information, and to define governance to ensure data quality.
From the corporate point of view, previously unused internal and external data must be integrated, stored, and analyzed on a big data platform to be actively utilized for quality management prediction and decision-making.
• In order to utilize data safely, it is necessary to consider various collection technologies along with review of which data is to be collected, how to collect it and where to store it.
• Data imported through data collection is classified according to the nature of data collection, and the classified data is stored and used for big data analysis.
• Data collection technologies such as Flume, Sqoop, Chukwa, Logstash, FileBeat, etc.
Open source has well-defined interfaces and considerations for overflow.
Source : Big data and public goods SW from the data point of view, 2013, National IT Industry Promotion Agency
