• Journal of KIISE
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• v.43 no.12
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• pp.1385-1395
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• 2016

In the era of Big Data, NoSQL databases provide solutions for problems, circumventing the limitations of traditional relational databases by using new architectures and data model. Contrary to relational database products, the range of the features architectures, and limitations of NoSQL databases is very broad. Thus, choosing the right database products requires more considerations and difficulties. The advent of NoSQL does not only promote the abundance of NoSQL products, but also stimulates the relational database realm to expand their features beyond the relational model. In order to understand NoSQL trends more accurately, here we discuss and compare NoSQL databases with relational databases. We also present the newest features associated with NoSQL in one of the most advanced open-source relational databases, PostgreSQL. To discuss future directions for PostgreSQL we analyzed the performance of NoSQL and PostgreSQL by conducting experiments using the NoSQL benchmark tool (YCSB).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.351-354
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• 2014

The emergence of big data has brought many changes to the database management environment. the each amount of big data will increase, but each data size is smaller and simpler. This feature was required to a new data processing techniques. Accordingly, A variety database technology was provided to Specializing in big data processing. It is defined as NoSQL. NoSQL is how to use each different, according to the data characteristics. It is difficult to define one. In this paper, Classified according to the characteristics of each type of NoSQL Appropriate NoSQL is proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2067-2075
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• 2017

Lately big data processing is considered as an emerging issue. As a huge amount of data is generated, data processing capability is getting important. In processing big data, both Hadoop distributed file system and unstructured date processing-based NoSQL data store are getting a lot of attention. However, there still exists problems and inconvenience to use NoSQL. In case of low volume data, MapReduce of NoSQL normally consumes unnecessary processing time and requires relatively much more data retrieval time than RDBMS. In order to address the NoSQL problem, in this paper, an interworking scheme between NoSQL and the conventional RDBMS is proposed. The developed auto-mapping scheme enables to choose an appropriate database (NoSQL or RDBMS) depending on the amount of data, which results in fast search time. The experimental results for a specific data set shows that the database interworking scheme reduces data searching time by 35% at the maximum.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.455-464
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• 2020

With a variety of data types and high utilization of data, non-relational databases are a popular data storage because it supports better availability and scalability. The increasing use of this technology also brings the risk of NoSQL injection attacks. Existing works mostly discuss the rule-based detection of NoSQL injection attacks that it is hard to deal with NoSQL queries beyond the coverage of the rules. In this paper, we propose a model for detecting NoSQL injection attacks. Our model is based on deep learning algorithms that select features from NoSQL queries using CNN, and classify NoSQL queries using RNN. Also, we experiment the proposed model to compare with existing models, and find that our model outperforms traditional models in terms of detection rate.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.431-434
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• 2014

웹서비스 사용이 보편화되면서 웹 애플리케이션의 보안취약점을 악용하는 해커들이 늘어나고 있다. 악의적인 공격으로 인한 피해를 막기 위해 보안을 견고하게 하지만 보안취약점에 의한 피해가 빈번하게 발생하고 있다. 본 논문에서는 이러한 보안취약점 중 SQL Injection 취약점과 NoSQL Injection 취약점을 분석하고, 침투 시험을 통해 사용자의 최소한의 개입만으로 SQL Injection 취약점과 NoSQL Injection 취약점을 자동으로 탐지하는 도구의 설계 방법을 제안한다. 제안한 도구는 SQL Injection 취약점과 NoSQL Injection 취약점을 탐지하기 위한 전문적인 보안 지식을 요구하지 않기 때문에 자동 침투 시험 도구를 사용하면 보안 비전문가도 쉽게 취약점을 탐지할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.867-869
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• 2015

최근 폭발적으로 증가하는 데이터양과 데이터 특성들로 인해 관계형 데이터베이스는 빅데이터 처리에 어려움이 발생하기 시작했으며, 이러한 빅데이터의 신속한 처리를 위해 비정형 데이터 분산처리, 병렬 처리 등 특정한 영역에서 우수한 성능을 보이는 NoSQL 데이터베이스의 활용이 증가하고 있다. 기존 관계형 데이터베이스에서 악의적인 SQL Injection 공격이 시스템에 치명적인 피해를 주는 것과 마찬가지로, 다른 쿼리 언어를 사용하는 NoSQL 데이터베이스에서도 Injection 공격에 대한 취약점이 여전히 존재할 뿐만 아니라, NoSQL 데이터베이스가 비교적 최신 기술이기 때문에 개발자들은 Injection 공격에 대한 인식이 부족한 실정이다. 본 논문에서는 NoSQL 데이터베이스에 대한 대표적인 2가지 Injection 공격 방법을 소개하고, "NoSQL Injection Defender(NID)"라 명명한 Injection 공격 방어 시스템의 설계 방안을 제시하고자 한다.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.299-306
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• 2015

In this paper, we research to secure stability of data storing/searching on NoSQL implemented on Distributed File System. When implementing NoSQL on Distributed File System, we faced that random write on Distributed File System is almost impossible. To solve this problem, a concept of Intermediate-File was employed, and then it has been achieved that our system resist any failure circumstance. Additionally, since we discovered its performance cannot be as fast as general File System, by redefining the file block unit for our NoSQL system, we have prevented a slowdown in system performance. As a result, we are able to develop highly scalable NoSQL as Distributed File System, which fulfills basic conditions of transaction: Atomicity, Consistency, Isolation, and Performance.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.107-115
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• 2022

Recently, big data applications need another database different from the Relation database. NoSQL databases are used to save and handle massive amounts of data. NoSQL databases have many advantages over traditional databases like flexibility, efficiently processing data, scalability, and dynamic schemas. Most of the current applications are based on the web, and the size of data is in increasing. NoSQL databases are expected to be used on a more and large scale in the future. However, NoSQL suffers from many security issues, and one of them is access control. Many recent applications need Fine-Grained Access control (FGAC). The integration of the NoSQL databases with FGAC will increase their usability in various fields. It will offer customized data protection levels and enhance security in NoSQL databases. There are different NoSQL database models, and a document-based database is one type of them. In this research, we choose the CouchDB NoSQL document database and develop an access control mechanism that works at a fain-grained level. The proposed mechanism uses role-based access control of CouchDB and restricts read access to work at the document level. The experiment shows that our mechanism effectively works at the document level in CouchDB with good execution time.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.95-104
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• 2017

As the technology in smart device is growing and Social Network Services(SNS) are becoming more common, the data which is difficult to be processed by existing RDBMS are increasing. As a result of this, NoSQL databases are getting popular as an alternative for processing massive and unstructured data generated in real time. The demand for the technique of digital investigation of NoSQL databases is increasing as the businesses introducing NoSQL database in their system are increasing, although the technique of digital investigation of databases has been researched centered on RDMBS. New techniques of digital forensic investigation are needed as NoSQL Database has no schema to normalize and the storage method differs depending on the type of database and operation environment. Research on document-based database of NoSQL has been done but it is not applicable as itself to other types of NoSQL Database. Therefore, the way of operation and data model, grasp of operation environment, collection and analysis of artifacts and recovery technique of deleted data in HBase which is a NoSQL column-based database are presented in this paper. Also the proposed technique of digital forensic investigation to HBase is verified by an experimental scenario.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.89-90
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• 2021

최근 증가하고 있는 대용량, 비정형 데이터의 처리를 위해 NoSQL의 사용이 증가하고 있다. 하지만 기존의 소프트웨어들은 대부분 RDBMS로 구성되어있고, 저용량 데이터의 경우 RDBMS를 사용하여 관리하는 경우가 많다. 때문에 기존 RDBMS를 사용한 소프트웨어를 대용량 처리에 유리하도록 NoSQL 기반으로 마이그레이션하여 새로운 버전을 개발하고, 각각의 이점을 효율적으로 사용하기 위해 RDBMS와 NoSQL의 혼용하는 사례가 증가하고있다. 본 논문에서는 RDBMS와 NoSQL간의 데이터 매핑 관리 모델을 제안하여 소프트웨어 개발자 또는 데이터 관리자의 효율적 데이터 관리에 도움을 준다.