• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.417-428
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• 2020

With the rapid development of information and communication technology, mobile devices have become an essential tool in our lives. Mobile devices are used as important evidence in criminal proof, as they accumulate data simultaneously with PIM functions while working with users most of the time. The mobile forensics is a procedure for obtaining digital evidence from mobile devices and should be collected and analyzed in accordance with due process, just like other evidence, and the integrity of the evidence is essential because it has aspects that are easy to manipulate and delete. Also, the adoption of evidence relies on the judges' liberalism, which necessitates the presentation of generalized procedures. In this paper, a mobile forensics model is presented to ensure integrity through the generalization of procedures. It is expected that the proposed mobile forensics model will contribute to the formation of judges by ensuring the reliability and authenticity of evidence.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.887-892
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• 2011

Recently iPad has been released, so users interest in new portable device is increasing. As markets grow, experts are forecasting a increase of investigation about tablet PC. However iPad forensics is very difficult using existing smart phone forensic softwares. especially, those softwares can't analyze korean mobile application. This paper describes collecting/analyzing technique for iPad.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.671-685
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• 2023

By applying artificial intelligence to image editing technology, it has become possible to generate high-quality images with minimal traces of manipulation. However, since these technologies can be misused for criminal activities such as dissemination of false information, destruction of evidence, and denial of facts, it is crucial to implement strong countermeasures. In this study, image file and mobile forensic artifacts analysis were conducted for detecting image manipulation. Image file analysis involves parsing the metadata of manipulated images and comparing them with a Reference DB to detect manipulation. The Reference DB is a database that collects manipulation-related traces left in image metadata, which serves as a criterion for detecting image manipulation. In the mobile forensic artifacts analysis, packages related to image editing tools were extracted and analyzed to aid the detection of image manipulation. The proposed methodology overcomes the limitations of existing graphic feature-based analysis and combines with image processing techniques, providing the advantage of reducing false positives. The research results demonstrate the significant role of such methodology in digital forensic investigation and analysis. Additionally, We provide the code for parsing image metadata and the Reference DB along with the dataset of manipulated images, aiming to contribute to related research.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.39-46
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• 2012

In this paper, for the cloud system by explaining how the forensic aspects of the investigation. Smartphone Growth Entering a variety of applications were developed which cloud systems of personal information and information assets sharing applications as during incidents on the case evidence collection, an important factor, whereas such systematic investigative methods, born in the course of my investigation of the can be confusing. This paper on the forensic aspects of the cloud system by proposing a crime scene investigation procedures, investigative support, and aiding in the systematic collection of data to support evidence.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.73-83
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• 2014

Thanks to the development of diverse audio editing Technology, audio file can be easily revised. As a result, diverse social problems like forgery may be caused. Digital forensic technology is actively studied to solve these problems. In this paper, a hand-held device identification method, an area of digital forensic technology is proposed. It uses the noise features of devices caused by the design and the integrated circuit of each device but cannot be identified by the audience. Wiener filter is used to get the noise sounds of devices and their acoustic features are extracted via MIRtoolbox and then they are trained by multi-layer neural network. To evaluate the proposed method, we use 5-fold cross-validation for the recorded data collected from 6 mobile devices. The experiments show the performance 99.9%. We also perform some experiments to observe the noise features of mobile devices are still useful after the data are uploaded to UCC. The experiments show the performance of 99.8% for UCC data.

• Mass Spectrometry Letters
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• v.9 no.4
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• pp.95-99
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• 2018

An innovative, simple, and rapid assay method based on liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was developed and validated for the simultaneous determination of eight statin drugs in human urine. A simple sample clean-up procedure using the "dilute and shoot" (DAS) approach enabled a fast and reliable analysis. The influence of the dilution factor was investigated to ensure detectability and reduce the matrix effect. Chromatographic separation was performed on a Phenomenex Kinetex C18 column ($50{\times}3.0mm$ i.d., $2.6{\mu}m$) using an elution gradient of mobile phase A composed of 0.1% acetic acid, and mobile phase B composed of acetonitrile, at a flow rate of 0.35 mL/min. Quantitation was performed on a triple quadrupole mass spectrometer operated in multiple reaction monitoring (MRM) mode using electrospray ionization in positive ion mode. The total chromatographic run time was 15 min. The method was validated for selectivity, sensitivity, recovery, linearity, accuracy, precision, and stability. The present method was successfully applied to the analysis of Rosuvastatin in urine samples after oral administration to healthy human subjects.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.625-633
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• 2018

Realm is an open source database developed to replace SQLite, which is commonly used in mobile devices. The data stored in the database must be checked during the digital forensic analysis process for mobile devices because it can help to understand the behavior of the user and whether the mobile device is operating or not. In addition, since the user can intentionally use anti-forensic techniques such as deleting data stored in the database, research on how to recover deleted records is needed. In this paper, we propose a method to recover records that have not been overwritten after deletion based on the analysis of the structure and record and deletion process of the Realm database file.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.151-166
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• 2009

To prove the integrity of digital evidence on the investigation procedure, the data which is using the MD 5(Message Digest 5) hash-function algorithm has to be discarded, if the integrity was damaged on the investigation. Even though a proof restoration of the deleted area is essential for securing the proof regarding a main phase of a case, it was difficult to secure the decisive evidence because of the damaged evidence data due to the difference between the overall hash value and the first value. From this viewpoint, this paper proposes the novel model for the mobile forensic procedure, named as "E-Finder(Evidence Finder)", to ,solve the existing problem. The E-Finder has 5 main phases and 15 procedures. We compared E-Finder with NIST(National Institute of Standards and Technology) and Tata Elxsi Security Group. This paper thus achieved the development and standardization of the investigation methodology for the mobile forensics.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.280-287
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• 2022

Recently, the number of mobile ransomware types has increased. Moreover, the number of cases of damage caused by mobile ransomware is increasing. Representative damage cases include encrypting files on the victim's smart device or making them unusable, causing financial losses to the victim. This study classifies ransomware apps by analyzing several representative ransomware apps to identify trends in the malicious behavior of ransomware. We present a technique for recovering from the damage, from a digital forensic perspective, using reverse engineering ransomware apps to analyze vulnerabilities in malicious functions applied with various cryptographic technologies. Our study found that ransomware applications are largely divided into three types: locker, crypto, and hybrid. In addition, we presented a method for recovering the damage caused by each type of ransomware app using an actual case. This study is expected to help minimize the damage caused by ransomware apps and respond to new ransomware apps.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.402-410
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• 2022

Digital data can be manipulated easily, so information related to the timestamp is important in establishing the reliability of the data. The time values for a certain file can be extracted following the analysis of the filesystem metadata or file internals, and the information can be utilized to organize a timeline for a digital investigation. Suppose the reversal of a timestamp is found on a mobile device during this process. In this case, a more detailed analysis is required due to the possibility of anti-forensic activity, but little previous research has investigated the handling and possible manipulation of timestamps on mobile devices. Therefore, in this study, we determine how time values for multimedia files are handled according to the operating system or filesystem on mobile devices. We also discuss five types of timestamps-file created (C), last modified (M), last accessed (A), digitalized (Di), and filename (FN) of multimedia files, and experimented with their operational features across multiple devices such as smartphones and cameras.