• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.869-879
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• 2022

Through this study, we discovered that among three types of compressed data blocks generated through the Deflate algorithm, No-Payload Non-Compressed Block type (NPNCB) which has no literal data can be randomly generated and inserted between normal compressed blocks. In the header of the non-compressed block, there is a data area that exists only for byte alignment, and we called this area as DBA (Disposed Bit Area), where an attacker can hide various malicious codes and data. Finally we found the vulnerability that hides malicious codes or arbitrary data through inserting NPNCBs with infected DBA between normal compressed blocks according to a pre-designed attack scenario. Experiments show that even though contaminated NPNCB blocks were inserted between normal compressed blocks, commercial programs decoded normally contaminated zip file without any warning, and malicious code could be executed by the malicious decoder.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.410-421
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• 2019

Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS have been carried out recently. In many practical applications, there is no prior information except for standard sparsity on signals. The typical example is the sparse signals have block-sparse structures whose non-zero coefficients occurring in clusters, while the cluster pattern is usually unavailable as the prior information. To discuss this issue, a new algorithm, called backtracking-based adaptive orthogonal matching pursuit for block distributed compressed sensing (DCSBBAOMP), is proposed. In contrast to existing block methods which consider the single-channel signal reconstruction, the DCSBBAOMP resorts to the multi-channel signals reconstruction. Moreover, this algorithm is an iterative approach, which consists of forward selection and backward removal stages in each iteration. An advantage of this method is that perfect reconstruction performance can be achieved without prior information on the block-sparsity structure. Numerical experiments are provided to illustrate the desirable performance of the proposed method.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.207-216
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• 2023

For decoding-compatible parallel Deflate algorithm, this study proposed a new method of the control header being made in such a way that essential information for parallel compression and decompression are stored in the Disposed Bit Area (DBA) of the non-compression block and being inserted into the compressed blocks. Through this, parallel compression and decompression are possible while maintaining perfect compatibility with the existing decoder. After applying this method, the compression time was reduced by up to 71.2% compared to the sequential processing method, and the parallel decompression time was reduced by up to 65.7%. In particular, it is well known that parallel decompression is impossible due to the structural limitations of the Deflate algorithm. However, the decoder equipped with the proposed method enables high-speed parallel decompression at the algorithm level and maintains compatibility, so that parallelly compressed data can be decoded normally by existing decoder programs.

• Journal of the Korea Concrete Institute
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• v.15 no.2
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• pp.335-343
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• 2003

In the previous experimental study, it is verified that the ultimate strain of concrete (${\varepsilon}$$_{cu}$=0.003) and coefficient of equivalent stress block (${\beta}$$_1$) can be used for the analysis of RC beams under biaxial and uniaxial bending moment. However, the characteristics of stress distribution of non rectangular compressed area in the RC columns are different to those of rectangular compressed area. The properties of compressive stress distribution of concrete have minor effect on the pure bending moment such as beams, but for the columns subjected to combined axial load and biaxial bending moment, the properties of compressive stress distribution are influencing factors. Nevertheless, in ACI 318-99 code, the design tables for columns subjected to axial loads with bidirectional eccentricities are based on the parameters recommended for rectangular stress block(RSB) of rectangular compressed areas. In this study the characteristics of stress distribution through both angle and depth of neutral axis are observed and formulated rationally. And the modified parameters of rectangular stress block(MRSB) for non rectangular compressed area is proposed. And the computer program using MRSB for the biaxial bending analysis of RC columns is developed and the results of MRSB are compared to RSB and experimental results respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1499-1513
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• 2014

This paper proposes a novel blind image watermarking scheme exploiting Block Truncation Coding (BTC). Most of existing BTC-based watermarking or data hiding methods embed information in BTC compressed images by modifying the BTC encoding stage or BTC-compressed data, resulting in watermarked images with bad quality. Other than existing BTC-based watermarking schemes, our scheme does not really perform the BTC compression on images during the embedding process but uses the parity of BTC quantization data to guide the watermark embedding and extraction processes. In our scheme, we use a binary image as the original watermark. During the embedding process, the original cover image is first partitioned into non-overlapping $4{\times}4$ blocks. Then, BTC is performed on each block to obtain its BTC quantized high mean and low mean. According to the parity of high mean and the parity of low mean, two watermark bits are embedded in each block by modifying the pixel values in the block to make sure that the parity of high mean and the parity of low mean in the modified block are equal to the two watermark bits. During the extraction process, BTC is first performed on each block to obtain its high mean and low mean. By checking the parity of high mean and the parity of low mean, we can extract the two watermark bits in each block. The experimental results show that the proposed watermarking method is fragile to most image processing operations and various kinds of attacks while preserving the invisibility very well, thus the proposed scheme can be used for image authentication.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.11-19
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• 1999

Fractal image compression algorithm has been studied mostly not in the view of hardware but software. However, a general processor by software can't decode fractal compressed images in real-time. Therefore, it is necessary that we develop a fast dedicated hardware. However, design examples of dedicated hardware are very rare. In this paper, we designed a quadtree fractal-based compressed image decoder which can decode $256{\times}256$ gray-scale images in real-time and used two power-down methods. The first is a hardware-optimized simple post-processing, whose role is to remove block effect appeared after reconstruction, and which is easier to be implemented in hardware than non-2' exponents weighted average method used in conventional software implementation, lessens costs, and accelerates post-processing speed by about 69%. Therefore, we can expect that the method dissipates low power and low energy. The second is to design a power dissipation in the multiplier can be reduced by about 28% with respect to a general array multiplier which is known efficient for low power design in the size of 8 bits or smaller. Using the above two power-down methods, we designed decoder's core block in 3.3V, 1 poly 3 metal, $0.6{\mu}m$ CMOS technology.

• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1069-1079
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• 2005

Though there have been many methods to detect features in spatial domain, in the case of a compressed image it has to be decoded, processed and encoded again. Alternatively, we can manipulate a compressed image directly in the Discrete Cosine Transform (DCT) domain that has been used for compressing videos or images in the standards like MPEG and JPEG. In our previous work we proposed a model-based discontinuity evaluation technique in the DCT domain that had problems in the rotated or non-ideal discontinuities. In this paper, we propose a fuzzy filtering technique that consists of height fuzzification, direction fuzzification, and forty filtering of discontinuities. The enhancement achieved by the fuzzy tittering includes the linking, thinning, and smoothing of discontinuities in the DCT domain. Although the detected discontinuities are rough in a low-resolution image for the size (8${\times}$8 pixels) of the DCT block, experimental results show that this technique is fast and stable to enhance the qualify of discontinuities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.360-373
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• 2017

This paper presents a novel digital video steganalysis scheme against the spatial domain video steganography technology based on a spatial temporal detector (ST_D) that considers both spatial and temporal redundancies of the video sequences simultaneously. Three descriptors are constructed on XY, XT and YT planes respectively to depict the spatial and temporal relationship between the current pixel and its adjacent pixels. Considering the impact of local motion intensity and texture complexity on the histogram distribution of three descriptors, each frame is segmented into non-overlapped blocks that are $8{\times}8$ in size for motion and texture analysis. Subsequently, texture and motion factors are introduced to provide reasonable weights for histograms of the three descriptors of each block. After further weighted modulation, the statistics of the histograms of the three descriptors are concatenated into a single value to build the global description of ST_D. The experimental results demonstrate the great advantage of our features relative to those of the rich model (RM), the subtractive pixel adjacency model (SPAM) and subtractive prediction error adjacency matrix (SPEAM), especially for compressed videos, which constitute most Internet videos.

• ETRI Journal
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• v.43 no.1
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• pp.109-119
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• 2021

Self-recovery is a tamper-detection and image recovery methods based on data hiding. It generates two types of data and embeds them into the original image: authentication data for tamper detection and reference data for image recovery. In this paper, a region-based scalable self-recovery (RSS) method is proposed for salient-object images. As the images consist of two main regions, the region of interest (ROI) and the region of non-interest (RONI), the proposed method is aimed at achieving higher reconstruction quality for the ROI. Moreover, tamper tolerability is improved by using scalable recovery. In the RSS method, separate reference data are generated for the ROI and RONI. Initially, two compressed bitstreams at different rates are generated using the embedded zero-block coding source encoder. Subsequently, each bitstream is divided into several parts, which are protected through various redundancy rates, using the Reed-Solomon channel encoder. The proposed method is tested on 10 000 salient-object images from the MSRA database. The results show that the RSS method, compared to related methods, improves reconstruction quality and tamper tolerability by approximately 30% and 15%, respectively.