• Annual Conference of KIPS
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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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.135-144
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• 2014

Since anti-forensics have been developed in order to avoid digital forensic investigation, the forensic methods for analyzing anti-forensic behaviors have been studied in various aspects. Among the factors for user activity analysis, "Iconcache.db" files, which have the icon information of applications, provides meaningful information for digital forensic investigation. This paper illustrates the features of IconCache.db files and suggests the countermeasures against anti-forensics utilizing them.

• Journal of Information Science Theory and Practice
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• v.11 no.4
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• pp.14-39
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• 2023

Cybercrime is a significant threat to Internet users, involving crimes committed using computers or computer networks. The landscape of cyberspace presents a complex terrain, making the task of tracing the origins of sensitive data a formidable and often elusive endeavor. However, tracing the source of sensitive data in online cyberspace is critically challenging, and detecting cyber-criminals on the other hand remains a time-consuming process, especially in social networks. Cyber-criminals target individuals for financial gain or to cause harm to their assets, resulting in the loss or theft of millions of user data over the past few decades. Forensic professionals play a vital role in conducting successful investigations and acquiring legally acceptable evidence admissible in court proceedings using modern techniques. This study aims to provide an overview of forensic investigation methods for extracting digital evidence from computer systems and mobile devices to combat persistent cybercrime. It also discusses current cybercrime issues and mitigation procedures.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.4
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• pp.95-102
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• 2016

Computer security incident such as confidential information leak and data destruction are constantly growing and it becomes threat to information in digital devices. To respond against the incident, digital forensic techniques are also developing to help digital incident investigation. With the development of digital forensic technology, a variety of forensic artifact has been developed to trace the behavior of users. Also, a diversity of forensic tool has been developed to extract information from forensic artifact. However, there is a issue that information from forensic tools has its own forms. To solve this problem, it needs to process data when it is output from forensic tools. Then it needs to compare and analyze processed data to identify how data is related each other and interpret the implications. To reach this, it calls for effective method to store and output data in the course of data processing. This paper aims to propose DFIOC (Digital Forensic Indicators Of Compromise) that is capable of transcribing a variety of forensic artifact information effectively during incident analysis and response. DFIOC, which is XML based format, provides "Evidence" to represent various forensic artifacts in the incident investigation. Furthermore, It provides "Forensic Analysis" to report forensic analysis result and also gives "Indicator" to investigate the trace of incidence quickly. By logging data into one sheet in DFIOC format for forensic analysis process, it is capable of avoiding unnecessary data processing. Lastly, since collected information is recorded in a normalized format, data input and output becomes much easier as well as it will be convenient to use for identification of collected information and analysis of data relationship.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.91-105
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• 2014

This paper proposes a digital forensic method by an evaluation function based on timestamp changing patterns. Operations on file or folder leave changed timestamps, which give the ways to know what operations were executed. Changes of timestamps of ten operations of a file and eight operations of a folder were examined. Analyses on the changes on the eight folder operations are newly added in this paper, which are not performed in the previous works. Based on the timestamps changes of the file and the folder, two evaluation functions are proposed. The first evaluation function checks whether timestamps are changed by file and folder operations, and the second evaluation function checks whether timestamps are originated from a source file or other attribute field. By the two output values from these evaluation functions, a digital forensic investigation on the file or the folder is performed. With some cases, i. e. file copy and folder creation operations, the proposed forensic method is tested for its usefulness.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1212-1219
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• 2011

As recently Privacy Acts in Korea enforced in domestic companies' personal information management needs of a growing obligation for the safety measures and the right of personal information collection, use, limitations, management, and destroyed specifically for handling personal information. Such this regulations should be required technical and policy supports. Accordingly, for the enterprise incident has occurred, the personal information management system behave correctly operating to verify that the safety measures taken, and be determined by the specific preparation to be done. So the first, preparation phase corresponds to the upcoming digital forensic investigation model. On the other hand, the response team also carried these measures out correctly, it needs to be done to check the compliance of Privacy Act. Thus a digital forensics investigation model is strictly related with the implementation of the Privacy Acts and improve the coping strategies are needed. In this paper, we suggest a digital forensic investigation model corresponding to Privacy Act.

• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.39-59
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• 2024

An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.161-169
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• 2014

Digital forensics is the process of proving criminal charges by collecting and analyzing digital evidence which is related to the crime in question. Most digital forensic research is focused on digital forensic techniques themselves or cyber crime. In this paper, we designed a digital forensics-criminal investigation linked model in order to effectively apply digital forensics to various types of criminal investigations. Digital forensic ontology was developed based on this model. For more effective application of digital forensics to criminal investigation we derived specific application fields. The ontology has legality rules and adequacy rules, so it can support investigative decision-making. The ontology can be developed into an intelligent criminal investigation system.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.680-693
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• 2018

Nowadays, third-party applications form an important part of the mobile environment, and social networking applications in particular can leave a variety of user footprints compared to other applications. Digital forensics of mobile third-party applications can provide important evidence to forensics investigators. However, most mobile operating systems are now updated on a frequent basis, and developers are constantly releasing new versions of them. For these reasons, forensic investigators experience difficulties in finding the locations and meanings of data during digital investigations. Therefore, this paper presents scenario-based methods of forensic analysis for a specific third-party social networking service application on a specific mobile device. When applied to certain third-party applications, digital forensics can provide forensic investigators with useful data for the investigation process. The main purpose of the forensic analysis proposed in the present paper is to determine whether the general use of third-party applications leaves data in the mobile internal storage of mobile devices and whether such data are meaningful for forensic purposes.