• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.139-142
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• 2011

해외 기술 유출 사고로 인하여 한국 경제에 약 수조원의 피해가 발생하였다. 기업의 기술 유출과 사고 책임 소재를 증명하기 위한 e-Discovery시스템과 기업CERT/CC에 연구가 필요하다. 본 논문에서는 e-Discovery의 개념과 관련법안 및 권고안, 포렌식 수사절차에 대해 연구하고, 국내 e-Discovery 사고 사례와 해외 e-Discovery 사고 사례를 연구한다. e-Discovery가 도입되면 기업 CERT/CC에서 필요한 e-Discovery 시스템을 설계한다. e-Discovery 시스템의 접근과 인증을 위한 사용자인증과 기기 인증에 대한 기술과 암호화 기술을 연구한다. 본 논문 연구를 통하여 e-Discovery 제도의 도입과 포렌식 기술 발전에 기초자료로 활용될 것이다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.51-58
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• 2019

Temporal analysis is very useful and important for digital forensics for reconstructing the timeline of digital events. Forgery of a file's timestamp can lead to inconsistencies in the overall temporal relationship, making it difficult to analyze the timeline in reconstructing actions or events and the results of the analysis might not be reliable. The purpose of the timestamp change is to hide the data in a steganographic way, and the other purpose is for anti-forensics. In both cases, the time stamp change tools are requested to use. In this paper, we propose a classification method based on the behavior of the timestamp change tools. The timestamp change tools are categorized three types according to patterns of the changed timestamps after using the tools. By analyzing the changed timestamps, it can be decided what kind of tool is used. And we show that the three types of the patterns are closely related to API functions which are used to develop the tools.

• Convergence Security Journal
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• v.18 no.2
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• pp.25-32
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• 2018

As the use of smartphones become more common, the communication via instant messenger becomes natural. However, it is important to secure the relevant information promptly since the chat room between participants can be used as a space for a criminal conspiracy, and crime-related contents can be stored and deleted easily on smartphones. Therefore, this study aims to identify the available data and to use it as proof by comparing and analyzing the instant messengers with high usage rate.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• Journal of Auto-vehicle Safety Association
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• v.12 no.3
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• pp.52-60
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• 2020

Usage of EDR(Event Data Recorder) report for traffic accident analysis is currently increasing due to government regulation of EDR data release. Nevertheless, a lot of investigators simply adopt by comparing the number of ignition cycles(crash) at event to the number of ignition cycles(download) without an exact judgment whether event data occurred by this accident or not. In the EDR report, besides ignition cycles, there are many factors such as event record type, algorithm active(rear/rollover/side/frontal), time between events, event severity status(rollover/rear/right side/reft side/frontal), belt switch circuit status, driver/passenger pretensioner/air-bag deployment, PDOF(Principal Direction of Force) by ΔV to be able to decide whether or not to adopt. also the event data is considered enough to vehicle damaged state, accident situation at the scene of the accident. and there is described in "all data should be examined in conjunction with other available physical evidence from the vehicle and scene" in the CDR(Crash Data Retrieval) report. Therefore many investigators have to decide whether or not to adopt after they consider sufficiently to above factors when they are the traffic accident analysis and investigate the causes of a accident on the adopted event data. In this paper, we report to traffic accident investigators notable points and analysis methods on the basis of thousands of cases and the results of one's own experiment in NFS(National Forensic Service).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.737-751
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• 2023

The importance of digital forensics in the cloud environment is increasing as businesses and individuals move their data from On-premise to the cloud. Cloud data can be stored on various devices, including mobile devices and desktops, and encompasses a variety of user behavior artifacts, such as information generated from linked accounts and cloud services. However, there are limitations in securing and analyzing digital evidence due to environmental constraints of the cloud, such as distributed storage of data and lack of artifact linkage. One solution to address this is archiving services, and Google's Takeout is prime example. In this paper, user behavior data is analyzed for cloud forensics based on archiving data and necessary items are selected from an investigation perspective. Additionally, we propose the process of analyzing selectively collected data based on time information and utilizing web-based visualization to meaningfully assess artifact associations and multi-behaviors. Through this, we aim to demonstrate the value of utilizing archiving data in response to the increasing significance of evidence collection for cloud data.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.565-573
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• 2012

To investigate the business corruption, the obtainments of the business data such as personnel, manufacture, accounting and distribution etc., is absolutely necessary. Futhermore, the investigator should have the systematic extraction solution from the business data of the enterprise database, because most company manage each business data through the distributed database system, In the general business environment, the database exists in the system with upper layer application and big size file server. Besides, original resource data which input by user are distributed and stored in one or more table following the normalized rule. The earlier researches of the database structure analysis mainly handled the table relation for database's optimization and visualization. But, in the point of the digital forensic, the data, itself analysis is more important than the table relation. This paper suggests the extraction technique from the table relation which already defined in the database. Moreover, by the systematic analysis process based on the domain knowledge, analyzes the original business data structure stored in the database and proposes the solution to extract table which is related incident.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1662-1669
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• 2020

Google cloud includes data uploaded and synchronized by users, as well as synchronization history of all cloud services, users' smartphone usage, and location information. Therefore, Google cloud data can be useful for digital forensics from a user behavior analysis perspective. Through this paper, we have identified the types of cloud data that can be acquired using Google's Takeout service and developed a tool that can be usefully utilized in digital forensics research and investigation by screening and analyzing the data required for analyzing user behavior. Because Google cloud data is synchronized through Google accounts regardless of the type of computing device, Google service data used on various devices such as PCs, smartphones, and tablet PCs can be acquired through Google accounts without the device. Therefore, the results of this paper's research are expected to be very useful for digital forensics research and investigation in the current situation.

• Journal of Soil and Groundwater Environment
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• v.18 no.3
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• pp.1-10
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• 2013

This study was performed to summarize application of ${\delta}^{13}C$, ${\delta}^{37}Cl$ and ${\delta}D$ of trichloroethylene (TCE) to studies on environmental forensic field regarding identification of TCE sources and evaluation of contribution of TCE to groundwater using data collected from literatures. ${\delta}^{13}C$, ${\delta}^{37}Cl$ and ${\delta}D$ of TCE give some information regarding sources of TCE because they show specific value according to manufacturing method. Also, TCE do not show a significant isotopic fractionation owing to adsorption and dilution. The isotopic fractionation mainly occurs by biodegradation. In addition, isotopic fractionation factor for TCE is different according to a kind of microorganism participated in biodegradation. However, the isotopic data of TCE have to be applied with chemical compositions of TCE and other hydrogeologic factors because isotopic fractionation of TCE is influenced by various factors.