• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.59-66
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• 2017

MySQL database is the second place in the market share of the current database. Especially InnoDB storage engine has been used in the default storage engine from the version of MySQL5.5. And many companies are using the MySQL database with InnoDB storage engine. Study on the structural features and the log of the InnoDB storage engine in the field of digital forensics has been steadily underway, but for how to restore on a record-by-record basis for the deleted data, has not been studied. In the process of digital forensic investigation, database administrators damaged evidence for the purpose of destruction of evidence. For this reason, it is important in the process of forensic investigation to recover deleted record in database. In this paper, We proposed the method of recovering deleted data on a record-by-record in database by analyzing the structure of MySQL InnoDB storage engine. And we prove this method by tools. This method can be prevented by database anti forensic, and used to recover deleted data when incident which is related with MySQL InnoDB database is occurred.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.125-134
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• 2016

MySQL database is currently used by many users and It has gained a big market share in the database market. Even though MyISAM storage engine was used as a default storage engine before, but records recovery method does not existed. Deleted records have a high possibility for important evidence and it is almost impossible to determine that investigators manually examine large amounts of database directly. This paper suggests the universal recovery method for deleted records and presents the experimental results.

• Publications of The Korean Astronomical Society
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• v.19 no.1
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• pp.109-119
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• 2004

As a core project of the Korean Astronomical Data Center (KADC) in Korea Astronomy Observatory (KAO), we have constructed a framework of astronomical database using MySQL and JSP. MySQL database server is a powerful open source database management system, and JSP technology provides a simplified, fast way to create dynamic web content. Combined together, MySQL and JSP enable us to develop server-independent web-based applications efficiently in a short amount of time. The MySQL tables and JSP programs embedded in our database are built/written in a way to benefit both users and managers. We plan to expand our database by supplementing additional data in the near future. Our newly constructed database is expected to be the prototype of the Korean Virtual Observatory (KVO).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.631-634
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• 2014

When to build a Web and Cloud Computing environment, it is essential to used a database system. Database systems includes commercial programs, such as Oracle and MS-SQL, but also similar to the performance of commercial applications, there are many free programs. In particular, PostgreSQL, MySQL, MariaDB are no costs, but the source is open to the public can be applied to a variety of environments. This paper presents an open source relational database management system, the trends are examined.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.35-41
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• 2024

As online activities have rapidly increased due to recent digital changes and the impact of COVID-19, the importance of large-scale data processing and maintenance is increasing. This study compares the performance of the two main types of databases widely used for data storage and management: Relational Database Management Systems (RDBMS) and Non-Relational Databases (NoSQL). Specifically, we measured and evaluated the execution time of data insertion, query, and deletion functions using MySQL, a representative example of RDBMS, and Redis, a representative example of NoSQL. The experimental results showed that Redis showed performance about 5.84 times faster in data insertion, 6.61 times faster in query, and 12.33 times faster in deletion than MySQL. These results demonstrate that Redis provides superior performance, especially in environments requiring large-scale data processing and maintenance. Therefore, companies and online service providers can choose NoSQL databases such as Redis to ensure more efficient data management solutions. We hope this study will be an essential reference when selecting a database based on data processing performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.805-808
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• 2014

The DBMS is a database management software system to access by people. It is an open source DBMS, such as MySQL and commercial services, such as ORACLE. Since MySQL has been acquired by Oracle, MariaDB released increase demand. NoSQL also are increasing, the trend is of interest, depending on the circumstances. Based on the same type of mass data, Depending on the performance comparison between the open source DBMS is required, and The study compared the performance between MariaDB and MongoDB. This paper proposes a DBMS for big data to process.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.51-64
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• 2008

In general, R is useful for small size data. We study how to access a large data set in a database by R-language. We provide real examples to access data sets stored in database servers MySQL, Oracle or PostgreSQL.

• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.12
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• pp.487-496
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• 2017

In MySQL InnoDB, there are two ways of storing data. One is to create a separate tablespace for each table and store it separately. Another is to store all table and index information in a single system tablespace. You can use this information to recover deleted data from the record. However, in most of the current database forensic studies, the former is actively researched and its structure is analyzed, whereas the latter is not enough to be used for forensics. Both approaches must be analyzed in terms of database forensics because their storage structures are different from each other. In this paper, we propose a method for recovering deleted records in a method of storing records in IBDATA file, which is a single system tablespace. First, we analyze the IBDATA file to reveal its structure. And introduce delete record recovery algorithm which extended to an unallocated page area which was not considered in the past. In addition, we show that the recovery rate is improved up to 68% compared with the existing method through verification using real data by implementing the algorithm as a tool.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.139-142
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• 2008

While a lot of comparisons of DBMS performance for processing large scale database are given as results of bench-mark tests, there are few comparisons of DBMS performance for processing small scale database. Therefore, in this study, we compared and analyzed on the performance of commercial DBMS and public DBMS for small scale database. Analysis results show that while Oracle has low performance on the operations of update and insert due to the overhead of rollback for data safety, MySQL and MS-SQL have good performance without additional overhead.