• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.310-313
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• 2017

범죄수사 과정에서 많은 양의 데이터를 시간 내에 분석하는 것은 성공적인 포렌식의 필수 요소이다. 컴퓨터와 사람 모두에게 있어, 시간과 자원의 제한은 수사 결과에 부정적인 영향을 가져온다. 그러므로 현재 사용되고 있는 다양한 포렌식 도구에는 시간과 자원의 효율적인 사용이 필요하다. 사례기반추론 및 멀티에이전트 시스템과 같은 인공지능 기반의 도구를 통해 디지털 포렌식 수사를 효과적으로 도울 수 있다. 본 논문에서는 인공지능을 활용한 지능형 포렌식 도구 및 프레임워크를 분석하고, 오늘날의 프레임워크의 한계점과 미래에 관해 논의한다. 인공지능 기반 시스템의 목적은 수사에서의 증거를 포함한 데이터를 분석하고 연관성을 밝힘으로서 포렌식 전문가에게 중요한 단서를 제공하고 직접 분석해야하는 데이터의 양을 줄이는 것에 있다. 이러한 인공지능의 활용은 많은 양의 데이터를 수사할 때 사람이 간과할 수 있는 증거들을 연결시켜주는 데에 큰 도움이 된다.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.79-88
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• 2024

The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.111-122
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• 2018

Using OAuth protocol, third-party applications on the Android operating system use user's credentials or access tokens that have access authority on user's resources to gain user's account and personal information from account information providers. These credentials and token information are stored in the device by the OAuth data management method provided by the Android operating system. If this information is leaked, the attacker can use the leaked credential and token data to get user's personal data without login. This feature enables the digital forensic investigator to collect data directly from the remote server of the services used by the target of investigation in terms of collecting evidence data. Evidence data collected at a remote location can be a basis for secondary warranties and provide evidence which can be very important evidence when an attacker attempts to destroy evidence, such as the removal of an application from an Android device. In this paper, we analyze the management status of OAuth tokens in various Android operating system and device environment, and show how to collect data of various third party applications using it. This paper introduces a method of expanding the scope of data acquisition by collecting remote data of the services used by the subject of investigation from the viewpoint of digital forensics.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.271-274
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• 2017

점차 늘어나는 클라우드 서비스 이용률과 더불어 보안 위협 또한 증가하고 공격 방법 또한 다양해지고 있다. 하지만 클라우드 환경에서 보안사고가 발생했을 시 대응을 위한 조치나 정책은 여전히 미흡한 실정이다. 보안사고 대응을 위한 디지털 포렌식에 대한 연구를 통해 많은 해결 방법이 제시되고 있으나 클라우드 환경에서는 가상화 기술이 적용되어 있어 기존의 방법으로 증거의 수집 및 보관에 대한 무결성 증명이 까다롭다. 본 논문에서는 클라우드 서비스 이용자가 제공자로부터 서비스를 제공받는 클라우드 환경에서 보안사고 사후 대응을 위해 클라우드 환경에서 포렌식 절차를 수행 시 제안하는 참조모델을 바탕으로 필요한 역할 및 보안 고려사항에 대해 다루고자 한다.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.63-68
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• 2013

Recently, companies seek a way to overcome their financial crisis by reducing costs in the field of IT. In such a circumstance, cloud computing is rapidly emerging as an optimal solution to the crisis. Even in a digital forensic investigation, whether users of an investigated system have used a cloud service is a very important factor in selecting additional investigated subjects. When a user has used cloud services, such as Daum Cloud and Google Docs, it is possible to connect to the could service from a remote place by acquiring the user's log-in information. In such a case, evidence data should be collected from the remote place for an efficient digital forensic investigation, and it is needed to conduct research on the collection and analysis of data from various kinds of cloud services. Thus, this study suggested a digital forensic framework considering cloud environments by investigating collection and analysis techniques for each cloud service.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.12
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• pp.487-496
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• 2017

In MySQL InnoDB, there are two ways of storing data. One is to create a separate tablespace for each table and store it separately. Another is to store all table and index information in a single system tablespace. You can use this information to recover deleted data from the record. However, in most of the current database forensic studies, the former is actively researched and its structure is analyzed, whereas the latter is not enough to be used for forensics. Both approaches must be analyzed in terms of database forensics because their storage structures are different from each other. In this paper, we propose a method for recovering deleted records in a method of storing records in IBDATA file, which is a single system tablespace. First, we analyze the IBDATA file to reveal its structure. And introduce delete record recovery algorithm which extended to an unallocated page area which was not considered in the past. In addition, we show that the recovery rate is improved up to 68% compared with the existing method through verification using real data by implementing the algorithm as a tool.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.61-70
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• 2011

Virtualization is a technology that uses a logical environment to overcome physical limitations in hardware. As a part of cost savings and green IT policies, there is a tendency in which recent businesses increase the adoption of such virtualization. In particular, regarding the virtualization in desktop, it is one of the most widely used technology at the present time. Because it is able to efficiently use various types of operating systems in a physical computer. A virtual machine image that is a key component of virtualization is difficult to investigate. because the structure of virtual machine image is different from hard disk image. Therefore, we need researches about appropriate investigation procedure and method based on technical understanding of a virtual machine. In this research, we suggest a procedure of investigation on a virtual machine image and a method for a corrupted image of the VMware Workstation that has the largest number of users.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.279-290
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• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.107-122
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• 2017

Nowadays, digital forensic experts are not only computer experts who restore and find deleted files, but also general experts who posses various capabilities including knowledge about processes/laws, communication skills, and ethics. However, there have been few studies about qualifications or competencies required for digital forensic experts comparing with their importance. Therefore, in this study, AHP questionnaires were distributed to digital forensic experts and analyzed to derive priorities of competencies; the first-tier questions which consisted of knowledge, technology, and attitude, and the second-tier ones which have 20 items. Research findings showed that the most important competency was knowledge, followed by technology and attitude but no significant difference was found. Among 20 items of the second-tier competencies, the most important competency was "digital forensics equipment/tool program utilization skill" and it was followed by "data extraction and imaging skill from storage devices." Attitude such as "judgment," "morality," "communication skill," "concentration" were subsequently followed. The least critical one was "substantial law related to actual cases." Previous studies on training/education for digital forensics experts focused on law, IT knowledge, and usage of analytic tools while attitude-related competencies have not given proper attention. We hope this study can provide helpful implications to design curriculum and qualifying exam to foster digital forensic experts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3068-3086
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• 2022

Digital Forensics is gaining popularity in adjudication of criminal cases as use of electronic gadgets in committing crime has risen. Traditional approach to collecting digital evidence falls short when the disk is encrypted. Encryption keys are often stored in RAM when computer is running. An approach to acquire forensic data from RAM when the computer is shut down is proposed. The approach requires that the investigator immediately cools the RAM and transplant it into a host computer provisioned with a tool developed based on cold boot concept to acquire the RAM image. Observation of data obtained from the acquired image compared to the data loaded into memory shows the RAM chips exhibit some level of remanence which allows their content to persist after shutdown which is contrary to accepted knowledge that RAM loses its content immediately there is power cut. Results from experimental setups conducted with three different RAM chips labeled System A, B and C showed at a reduced temperature of -25C, the content suffered decay of 2.125% in 240 seconds, 0.975% in 120 seconds and 1.225% in 300 seconds respectively. Whereas at operating temperature of 25℃, there was decay of 82.33% in 60 seconds, 80.31% in 60 seconds and 95.27% in 120 seconds respectively. The content of RAM suffered significant decay within two minutes without power supply at operating temperature while at a reduced temperature less than 5% decay was observed. The findings show data can be recovered for forensic evidence even if the culprit shuts down the computer.