• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.143-154
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• 2011

SQLite is a small sized database engine largely used in embedded devices and local application software. The availability of portable devices, such as smartphones, has been extended over the recent years and has contributed to growing adaptation of SQLite. This implies a high likelihood of digital evidences acquired during forensic investigations to include SQLite database files. Where intentional deletion of sensitive data can be made by a suspect, forensic investigators need to recover deleted records in SQLite at the best possible. This study analyzes data management rules used by SQLite and the structure of deleted data in the system, and in turn suggests a recovery Tool of deleted data. Further, the study examines major SQLite suited software as it validates feasible possibility of deleted data recovery.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.390-391
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• 2016

SQLite is a database engine which is suitable for small devices that have large resource restriction and is used a lot in mobile devices based on Linux. SQLite is open source program and has advantages which are lighter weight and faster speed. This paper tests SQLite database performance of select in Linux environment, and analyzes the pros and cons of the results. The analysis is processed by comparison with the results of other database working out at the same environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.508-509
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• 2019

모바일 환경에서 데이터베이스 엔진 사용이 보편화되고 있으며 모바일에 적합한 데이터베이스 엔진 개발과 발표가 뒤따르고 있다. 모바일 데이터베이스는 대부분 플래시 메모리로 구성한 다양한 파일시스템에서 관리된다. 이 논문에서는 대표적인 모바일 데이터베이스인 SQLite3의 파일 시스템별 갱신 성능을 테스트한다. 그래서 각 파일 시스템별 특성을 파악하고 비교하기 위한 시스템을 구현하고 성능 실험을 실시한다. 실험 결과로부터 각 데이터베이스 갱신 패턴에 따른 파일 시스템별 장단점을 분석할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.108-110
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• 2018

In mobile IT device environments, it is becoming common to use database engine, and new mobile databases are continuously developed and announced. In this paper, the most common mobile database, SQLite3 is selected and experimented to test and understand the update performance and characteristics. The results of experiment are compared with the one of Oracle database at the same condition to evaluate the experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1571-1576
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• 2018

Recently, the attractive changes of mobile device are a improvement of the computing performance, dramatic improvement of storage capacity, constant connection to the internet, and sophisticated development of display technology. As a result, database applications utilizing mobile devices are emerging. These applications include databases for mobile servers, databases for edge computing, and fog computing. Therefore, it is important to pay attention to the current mobile database and pay attention to whether it has suitable performance for the applications. In this paper, the most common mobile database, SQLite3 is selected and experimented to test and understand the update performance and characteristics. The results of experiment are compared with the one of Oracle database at the same condition to evaluate the experiment. As a result, Insert Performance of SQLite3 has a lot of points to be improved and Update performance is very good. Especially, the performance of Range Query is excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1117-1122
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• 2020

The improving performance and utilizing application fields of mobile devices are getting bigger and wider. With this trend, applications that use database engines on mobile devices are also becoming common. Applications requiring mobile databases include mobile server databases, edge computing, fog computing, and the like. By the way, the most representative and widely used mobile database is SQLite3. In this paper, we test and compare the update performance of SQLite3 by some file systems. The update performance of the file systems in the mobile environment is an important performance factor in the limited H/W environment. The comparison file system was chosen as FAT, Ext2, and NTFS. Under the same conditions, experiments with each file system to test update performance and characteristics were processed. From the experimental results, we could analyze the advantages and disadvantages of each file system for each database update pattern.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.1-6
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• 2022

Recently, IoT sensors are often used to produce stream data locally and they are provided for edge computing applications. Mass-produced data are stored in the mobile device's database for real-time processing and then synchronized with the server when needed. Many mobile databases are developed to support those applications. They are CloudScape, DB2 Everyplace, ASA, PointBase Mobile, etc, and the most widely used database is SQLite3 on Linux. In this paper, we focused on the performance required for synchronization with the server. The search performance required to retrieve SQLite3 was compared and analyzed according to the type of each Linux file system in which the database is stored. Thus, performance differences were checked for each file system according to various search query types, and criteria for applying the more appropriate Linux file system according to the index use environment and table scan environment were prepared and presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3227-3235
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• 2011

In this paper, a relational embedded DBMS was designed and a prototype 'Miracle' RDBMS (MDB) was developed. MDB is written in C and works on Unix, Linux and Windows platforms locally. It accesses database through SQL interfaces and API functions and uses $B^+$ tree index. It guarantees ACID in transactions and supports low concurrency control and processes SQL statements on a single table. To evaluate the performance of MDB on an ARM board EZ-S3C6410 and to compare the performance of MDB with that of SQLite, an experiment was carried out to estimate processing times for insertion, selection, update and deletion operations. The result shows that the average times for selections and insertions in MDB were 38.46% and 22.86% faster than those in SQLite, respectively, but the average times for updates and deletions in SQLite were 28.33% and 26.00% faster than MDB, respectively, This experiment shows that fetching data from database and sending data to database in MDB is faster than in SQLite, but $B^+$ tree index is implemented more effectively in SQlite than in MDB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1557-1569
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• 2017

In recent times, the Internet of Things (IoT) has rapidly emerged as one of the most influential information and communication technologies (ICT). The various constituents of the IoT together offer novel technological opportunities by facilitating the so-called "hyper-connected world." The fundamental tasks that need to be performed to provide such a function involve the transceiving, storing, and analyzing of digital data. However, it is challenging to handle voluminous data with IoT devices because such devices generally lack sufficient computational capability. In this study, we examine the IoT from the perspective of security and digital forensics. SQLite is a light-weight database management system (DBMS) used in many IoT applications that stores private information. This information can be used in digital forensics as evidence. However, it is difficult to obtain critical evidence from IoT devices because the digital data stored in these devices is frequently deleted or updated. To address this issue, we propose Schema Pattern-based Recovery (SPaRe), an SQLite recovery scheme that leverages the pattern of a database schema. In particular, SPaRe exhaustively explores an SQLite database file and identifies all schematic patterns of a database record. We implemented SPaRe on an iPhone 6 running iOS 7 in order to test its performance. The results confirmed that SPaRe recovers an SQLite record at a high recovery rate.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.405-415
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• 2020

With the increase in smartphone user, mobile forensics has become an essential element in modern digital forensic investigation. Mobile messenger data is very important data in mobile forensics because it can acquire information such as user's life pattern and mental state. In order to analyze messenger data, a decryption technique of an encrypted messenger data is required. Since most messengers provide a message deleting function, a technique for recovering deleted messages is required. WeChat Messenger, a messenger used by about 1 billion people around the world, uses IMEI (International Mobile Equipment Identity) information to encrypt data and provides message deletion function. In this paper, we propose a data decryption method in the absence of IMEI information and propose a method for recovering deleted messages using FTS (Full Text Search) database created for full-text search function of SQLite database.