• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1107-1115
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• 2017

The most commonly used PKZIP format is a ZIP file, as well as a file format used in MS Office files and application files for Android smartphones. PKZIP format files, which are widely used in various areas, require structural analysis from the viewpoint of digital forensics and should be able to recover when files are damaged. However, previous studies have focused only on recovering data or extracting meaningful data using the Deflate compression algorithm used in ZIP files. Although most of the data resides in compressed data in the ZIP file, there is also forensically meaningful data in the rest of the ZIP file, so you need to restore it to a normal ZIP file format. Therefore, this paper presents a technique to recover a damaged ZIP file to a normal ZIP file when given.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.102-107
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• 2000

In general text compression techniques cannot be used directly in image compression because the model of text and image are different Recently, a new class of text compression, namely, block-sorting algorithm which involves Burrows and Wheeler transformation(BWT) gives excellent results in text compression. However, if we apply it directly into image compression, the result is poor. So, we propose simple method in order to improve the lossless compression performance of image. The proposed method can be divided into three steps. It is decomposed into ten subbands with the help of symmetric short kernel filter. The resulting subbands are block-sorted according to the method by BWT, and the redundancy is removed with the help of an adaptive arithmetic coder. Experimental results show that the proposed method is better than lossless JPEG and LZ-based compression method(PKZIP).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1259-1266
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• 2001

최근에 텍스트 압축에 뛰어난 성능을 가지는 블록 정렬 알고리즘인 BW변환 (Burrows-Wheeler Transform)이 소개되었다. 그러나 영상 압축에 BW변환을 직접 적용하면 영상과 텍스트가 갖는 상관성이 서로 다르기 때문에 만족할 만한 압축효과를 기대할 수 없게 된다. 따라서 본 논문에서는 가역의 L-SSKF(Lossless Symmetric Short Kernel Filter)를 사용한 계층적 대역분할로 영상화소 사이의 상관성을 줄인 후 BW변환을 하는 방법과 GAP(Gradient Adjusted Prediction)를 사용하여 LL 대역에 많이 분포된 상관성을 줄인 후 BW변환을 하는 방법을 제안한다. 실험결과 제안한 방법이 기존의 무손실 JPEG 표준안과 LZ 기반의 압축방법(PKZIP) 등에 비해 압축성능이 개선됨을 확인할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.31-41
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• 2012

The law enforcement agencies in the worldwide are confiscating or retaining computer systems involved in a crime/civil case, if there are any, at the preliminary investigation stage, even though the case does not involve a cyber-crime. They are collecting digital evidences from the suspects's systems and using them in the essential investigation procedure. It requires much time, though, to collect, duplicate and analyze disk images in general crime cases, especially in cases in which rapid response must be taken such as kidnapping and murder cases. The enterprise forensics, moreover, it is impossible to acquire and duplicate hard disk drives in mass storage server, database server and cloud environments. Therefore, it is efficient and effective to selectively collect only traces of the behavior of the user activities on operating systems or particular files in focus of triage investigation. On the other hand, if we acquire essential digital evidences from target computer, it is not forensically sound to collect just files. We need to use standard digital evidence container from various sources to prove integrity and probative of evidence. In this article, we describe a new digital evidence container, we called Xebeg, which is easily able to preserve collected digital evidences selectively for using general technology such as XML and PKZIP compression technology, which is satisfied with generality, integrity, unification, scalability and security.