• Title/Summary/Keyword: Forensics

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File Carving for Ext4 File System on Android OS (안드로이드 운영체제의 Ext4 파일 시스템에서 삭제 파일 카빙 기법)

  • Kim, Dohyun;Park, Jungheum;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.23 no.3
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    • pp.417-429
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    • 2013
  • A lot of OS(Operating Systems) such as Linux and Android selected Ext4 as the official file system. Therefore, a recovery of deleted file from Ext4 is becoming a pending issue. In this paper, we suggest how to recover the deleted file by analyzing the entire structure of Ext4 file system, the study of metadata area, the distinct feature when file is assigned and deleted. Particularly, we focus on studying the features of file which is assigned in Ext4 file system in Android OS and also suggest the method to recover the deleted file that is fragmented from the un-allocated area.

Software Montage: Filtering of Detecting Target of Similar Software for Digital Forensic Investigation (소프트웨어 몽타주: 디지털 포렌식 수사를 위한 유사 소프트웨어 탐지 대상의 필터링)

  • Park, Hee-Wan;Han, Tai-Sook
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.4
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    • pp.497-501
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    • 2010
  • A software montage means information that can be extracted quickly from software and includes inherent characteristics. If a montage is made from well-known programs, we can filter candidates of similar programs among the group of programs based on the montage. In this paper, we suggest software montages based on two characteristics: API calls and strings. To evaluate the proposed montages, we performed experiments to filter candidates of some similar programs to instant messenger programs. From the experiments, we confirmed that the proposed montages can be used as a forensic tool that filters a group of similar programs even when their functions are not known in advance.

Packed PE File Detection for Malware Forensics (악성코드 포렌식을 위한 패킹 파일 탐지에 관한 연구)

  • Han, Seung-Won;Lee, Sang-Jin
    • The KIPS Transactions:PartC
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    • v.16C no.5
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    • pp.555-562
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    • 2009
  • In malware accident investigation, the most important thing is detection of malicious code. Signature based anti-virus softwares have been used in most of the accident. Malware can easily avoid signature based detection by using packing or encryption method. Because of this, packed file detection is also important. Detection methods can be divided into signature based detection and entropy based detection. Signature based detection can not detect new packing. And entropy based detection has a problem with false positive. We provides detection method using entropy statistics of entry point section and 'write' properties of essential characteristic of packed file. And then, we show packing detection tool and evaluate its performance.

Practical and Legal Challenges of Cloud Investigations (클라우드 환경에서 수사 실무와 법적 과제)

  • James, Joshua I.;Jang, Yunsik
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.6
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    • pp.33-39
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    • 2014
  • An area presenting new opportunities for both legitimate business, as well as criminal organizations, is Cloud computing. This work gives a strong background in current digital forensic science, as well as a basic understanding of the goal of Law Enforcement when conducting digital forensic investigations. These concepts are then applied to digital forensic investigation of cloud environments in both theory and practice, and supplemented with current literature on the subject. Finally, legal challenges with digital forensic investigations in cloud environments are discussed.

Digital Forensics for Android Location Information using Hierarchical Clustering (계층적 군집화를 이용한 안드로이드 위치정보에 대한 디지털 포렌식)

  • Son, Youngjun;Chung, Mokdong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.6
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    • pp.143-151
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    • 2014
  • Recently, as smartphones are widespread, a variety of user's information is created and managed in smartphones. Especially the location information can show the user's position at a specific time and the user's area of interest, which could be very useful during criminal investigation. Although the location information plays an important role in solving the crimes such as serial murder, rape and arson cases, there is a lack of research on location information for digital forensics. In this paper, we analyze the location information from logs, images, and applications on android, and we suggest the integrated model for analyzing location information. The proposed model may be useful in criminal investigation by improving the efficiency of data analysis and providing information about a criminal case.

Classifier Combination Based Source Identification for Cell Phone Images

  • Wang, Bo;Tan, Yue;Zhao, Meijuan;Guo, Yanqing;Kong, Xiangwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.12
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    • pp.5087-5102
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    • 2015
  • Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

Method for Finding Related Object File for a Computer Forensics in a Log Record of $LogFile of NTFS File System (NTFS 파일시스템의 $LogFile의 로그레코드에 연관된 컴퓨터 포렌식 대상 파일을 찾기 위한 방법)

  • Cho, Gyu-Sang
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.4
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    • pp.1-8
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    • 2012
  • The NTFS journaling file($LogFile) is used to keep the file system clean in the event of a system crash or power failure. The operation on files leaves large amounts of information in the $LogFile. Despite the importance of a journal file as a forensic evidence repository, its structure is not well documented. The researchers used reverse engineering in order to gain a better understanding of the log record structures of address parts, and utilized the address for identifying object files to gain forensic information.

Alternate Data Stream Detection Method Using MFT Analysis Module on NTFS (MFT 분석기술을 이용한 Alternate Data Stream 탐지 기법)

  • Kim, Yo-Sik;Ryou, Jae-Cheol;Park, Sang-Seo
    • Convergence Security Journal
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    • v.7 no.3
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    • pp.95-100
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    • 2007
  • Alternate Data Streams (ADS) in NTFS originally has developed to provide compatibility with Macintosh Hierarchical File System. However, it is being used by the malware writers in order to support hiding malwares or data for the purpose of anti-forensics. Therefore identifying if hidden ADSs exist and extracting them became one of the most important component in computer forensics. This paper proposes a method to detect ADSs using MFT information. Experiment reveals that proposed method is better in performance and detection rate then others. This method supports not only identification of ADSs which are being used by the operating systems but also investigation of both live systems and evidence images. Therefore it is appropriate for using forensic purpose.

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Detection for Operation Chain: Histogram Equalization and Dither-like Operation

  • Chen, Zhipeng;Zhao, Yao;Ni, Rongrong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3751-3770
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    • 2015
  • Many sorts of image processing software facilitate image editing and also generate a great number of doctored images. Forensic technology emerges to detect the unintentional or malicious image operations. Most of forensic methods focus on the detection of single operations. However, a series of operations may be used to sequentially manipulate an image, which makes the operation detection problem complex. Forensic investigators always want to know as much exhaustive information about a suspicious image's entire processing history as possible. The detection of the operation chain, consisting of a series of operations, is a significant and challenging problem in the research field of forensics. In this paper, based on the histogram distribution uniformity of a manipulated image, we propose an operation chain detection scheme to identify histogram equalization (HE) followed by the dither-like operation (DLO). Two histogram features and a local spatial feature are utilized to further determine which DLO may have been applied. Both theoretical analysis and experimental results verify the effectiveness of our proposed scheme for both global and local scenarios.

Digital Forensics of Microsoft Office 2007-2013 Documents to Prevent Covert Communication

  • Fu, Zhangjie;Sun, Xingming;Xi, Jie
    • Journal of Communications and Networks
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    • v.17 no.5
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    • pp.525-533
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    • 2015
  • MS Office suit software is the most widely used electronic documents by a large number of users in the world, which has absolute predominance in office software market. MS Office 2007-2013 documents, which use new office open extensible markup language (OOXML) format, could be illegally used as cover mediums to transmit secret information by offenders, because they do not easily arouse others suspicion. This paper proposes nine forensic methods and an integrated forensic tool for OOXML format documents on the basis of researching the potential information hiding methods. The proposed forensic methods and tool cover three categories; document structure, document content, and document format. The aim is to prevent covert communication and provide security detection technology for electronic documents downloaded by users. The proposed methods can prevent the damage of secret information embedded by offenders. Extensive experiments based on real data set demonstrate the effectiveness of the proposed methods.