• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.123-134
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• 2014

As the data gets bigger recently, the demand for relational database management system (RDBMS) and NoSQL DBMS to process big data has been increased consistently. The digital forensic investigation method for RDBMS has been studied actively, but that for NoSQL DBMS, which is popularly used nowadays, has almost no research. This paper proposes the digital forensic investigation process and method for MongoDB, the most popularly used among NoSQL DBMS.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.469-476
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• 2016

Relational Database Management Systems have become de facto database model among most developers and users since the inception of Data Science. From IoT devices, sensors, social media and other sources, data is generated in structured, semi-structured and unstructured formats, in huge volumes, thereby the difficulty of data management greatly increases. Organizations that collect large amounts of data are increasingly turning to non relational databases - NoSQL databases. In this paper, through experiments with real field data, we demonstrate that MongoDB, a document-based NoSQL database, is a better alternative for building a Telco Subscriber Data Management System which hitherto is mainly built with Relational Database Management Systems. We compare the existing system in various phases of data flow with our proposed system powered by MongoDB. We show how various workloads at some phases of the existing system were either completely removed or significantly simplified on the new system. Based on experiment results, using MongoDB for managing telco subscriber data turned out to offer performance better than the existing system built with MSSQL Server.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.237-242
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• 2018

Recently, media data is increasing due to the development of Internet and SNS. Since photographs and videos often have geo-tags, many techniques have been developed to analyze them. In order to process various kind of such as SNS, NoSQL has been covered. However, most NoSQL does not have enough computation and query about spatial data. Therefore, in this paper, we designed and implemented a system for adding spatial operators using MongoDB among the representative NoSQL. Through this study, it is confirmed that various operators can be used and it is expected that various services can be performed using operators.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.133-136
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• 2019

본 고에서는 약 100 만건의 건강정보를 이용하여 3-Node MongoDB 플랫폼 환경에서 AES, 3DES, ARIA 암호 알고리즘을 이용하여 암호화를 적용하는 방법을 알아본다. 각각의 암호 알고리즘별로 YCSB 성능테스트 툴을 이용하여 다양한 Workload 별로 성능을 테스트를 수행한 뒤, 그 결과를 비교·정리한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.658-661
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• 2013

최근 데이터의 대용량화와 급격한 증가로 인해 빅데이터 처리를 위한 NoSQL DBMS 사용이 증가하고 있다. 그러나 기존 관계형 DBMS에 비해 NoSQL DBMS에 대한 포렌식 조사 기법에 대한 연구는 거의 없는 실적이다. 따라서, 본 논문에서는 NoSQL DBMS 중 가장 활발히 사용되고 있는 MongoDB에 대한 디지털 포렌식 조사 절차와 기법에 대해 연구하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.797-800
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• 2016

IoT가 다양한 형태로 IT 기술을 이용하는 사물의 서비스를 제공하고 있다. 보다 스마트한 IoT 환경을 만들기 위하여 센서 데이터를 효율적으로 컨트롤하는 시스템이 필요하다. 본 논문은 계속적으로 생성되는 IoT 센서 데이터 를 효율적으로 처리하는 시스템을 Loosely Coupled 하고 확장 가능한 Sensor Reaction System의 아키텍처로 구성하고 있다. 본 논문에서는 Node.js, MQTT, MongoDB 기술을 사용함으로써 이벤트 기반한 stream 및 batch 처리를 할 수 있도록 센서 데이터를 메시지 큐에서 효율적으로 처리한다. 본 논문에서는 아두이노 보드에 온도 및 빛 센서를 부착한 센서 디바이스로부터 센서 테이터를 받아서 PC 기반의 MQTT Broker / Sensor Reactor / MongoDB 서버 시스템을 구축하고 성능을 분석하였다.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.347-356
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• 2015

Due to the rapid development of IoT(Internet of Things) technology, traditional taxis are connected through dispatchers and location systems. Typically, modern taxis have embedded with GPS(Global Positioning System), which aims for obtaining the route information. By analyzing the frequency of taxi trip events, we can find the frequent route for a given query time. However, a scalability problem would occur when we convert the raw location data of taxi trip events into the analyzed frequency information due to the volume of location data. For this problem, we propose a NoSQL based top-K query system for taxi trip events. First, we analyze raw taxi trip events and extract frequencies of all routes. Then, we store the frequency information into hash-based index structure of MongoDB which is a document-oriented NoSQL database. Efficient top-K query processing for frequent route is done with the top of the MongoDB. We validate the efficiency of our algorithms by using real taxi trip events of New York City.

• Smart Media Journal
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• v.5 no.4
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• pp.124-130
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• 2016

Big data technologies are increasing the need for big data in many areas of the world. Recently, the health care industry has become increasingly aware of the importance of disease and health care services, as it has become increasingly immune to prevention and health care. To do this, we need a Big data system to collect and analyze the personal biometric data. In this paper, we design the biometric big data system using low cost wearable device. We collect basic biometric data, such as heart rate, step count and physical activity from Mi Band, and store the collected biometric data into MongoDB. Based on the results of this study, it is possible to build a big data system that can be used in actual medical environment by using Hadoop etc. and to use it in real medical service in connection with various wearable devices for medical information.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.957-959
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• 2013

A SNS(Social Networking Service) is an online platform to build social networks or social relations among people who, for example, share free communication, information, and make more personal connections. In this paper, we find representative entities, develop relationships among them, and draw an ERD based on the entities and their relationships. And then we design a SNS database schema by converting the ERD into collections according to data model of MongoDB, which is an NoSQL database.