• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.159-166
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• 2013

Recently, because the interest and needs in privacy protection are growing, smartcard-based remote user authentication schemes have been actively studied to provide the user anonymity. In 2008, Kim et al. first proposed an authentication scheme in order to ensure the user anonymity against both external attackers and the remote server and track malicious users with the help of a trusted trace sever. However, in 2010, Lee et al. showed that Kim et al.'s scheme cannot provide the user anonymity against remote server, which is because the server can trace users without any help of the trace server, and then proposed a improved scheme. On the other hand, in 2010, Horng et al. proposed an authentication scheme with non-tamper resistant smart cards, in which the non-tamper resistant smart card means that an attacker may find out secret information stored in the smart card through special data analysis techniques such as monitoring power consumption, to be secure against a variety of attacks and to provide the user anonymity against external attackers. In this paper, we will propose a remote user authentication scheme with non-tamper resistant smart cards not only to ensure the user anonymity against both external attackers and the remote server but also to track malicious users with only the help of a trusted trace sever.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1389-1403
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• 2021

Disaster management using VHR (very high resolution) satellite images supports rapid damage assessment and also offers detailed information of the damages. However, the acquisition of pre-event VHR satellite images is usually limited due to the long revisit time of VHR satellites. The absence of the pre-event data can reduce the accuracy of damage assessment since it is difficult to distinguish the changed region from the unchanged region with only post-event data. To address this limitation, in this study, we conducted the wildfire-induced change detection on national wildfire cases using post-fire VHR satellite images and GIS (Geographic Information System) data. For GIS data, a national land cover map was selected to simulate the pre-fire NIR (near-infrared) images using the spatial information of the pre-fire land cover. Then, the simulated pre-fire NIR images were used to analyze bi-temporal NDVI (Normalized Difference Vegetation Index) correlation for unsupervised change detection. The whole process of change detection was performed on a superpixel basis considering the advantages of superpixels being able to reduce the complexity of the image processing while preserving the details of the VHR images. The proposed method was validated on the 2019 Gangwon wildfire cases and showed a high overall accuracy over 98% and a high F1-score over 0.97 for both study sites.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.85-96
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• 2023

With advance of cloud computing technology, Blockchain as a Service of Cloud Service Provider has been utilized in various areas such as e-Commerce and financial companies to manage customer history and distribution history. However, if users' search history, purchase history, etc. are to be utilized in a BaaS in areas such as recommendation algorithms and search engine development, the users' search queries will be exposed to the company operating the BaaS, and privacy issues will be occured. Z. Guan et al. ensure the unlinkability between users' search query and search result using searchable encryption, and based on the inner product similarity, they select Top-k results that are highly relevant to the users' search query. However, there is a problem that the Top-k results selection may be not possible due to ties of inner product similarity, and BaaS over cloud is not considered. Therefore, this paper solve the problem of Z. Guan et al. using cosine similarity, so we improve accuracy of search result. And based on this, we design a BaaS with secure Top-k search that improved accuracy. Furthermore, we design a smart contracts that preserve privacy of users' search and obtain Top-k search results that are highly relevant to the users' search.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.12-31
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• 2006

The n-gram inverted index has two major advantages: language-neutral and error-tolerant. Due to these advantages, it has been widely used in information retrieval or in similar sequence matching for DNA and Protein databases. Nevertheless, the n-gram inverted index also has drawbacks: the size tends to be very large, and the performance of queries tends to be bad. In this paper, we propose the two-level n-gram inverted index (simply, the n-gram/2L index) that significantly reduces the size and improves the query performance while preserving the advantages of the n-gram inverted index. The proposed index eliminates the redundancy of the position information that exists in the n-gram inverted index. The proposed index is constructed in two steps: 1) extracting subsequences of length m from documents and 2) extracting n-grams from those subsequences. We formally prove that this two-step construction is identical to the relational normalization process that removes the redundancy caused by a non-trivial multivalued dependency. The n-gram/2L index has excellent properties: 1) it significantly reduces the size and improves the Performance compared with the n-gram inverted index with these improvements becoming more marked as the database size gets larger; 2) the query processing time increases only very slightly as the query length gets longer. Experimental results using databases of 1 GBytes show that the size of the n-gram/2L index is reduced by up to 1.9${\~}$2.7 times and, at the same time, the query performance is improved by up to 13.1 times compared with those of the n-gram inverted index.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.59-69
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• 2009

RFID tag search system which is used to find a specific tag has an application such as asset management, supply chain, and this search scheme has been given much attention so far. In RFID tag search system, especially, mobility of the reader is important in order to search tags. Therefore, even though the handheld reader cannot connect with the central database because of unreliable wireless connection or remote location, handheld reader should search the specific tag without help of the central database. In addition, in RFID tag search system, users hold not the tag but the reader, the privacy of users should be considered. Since the signal strength of the reader is stronger than that of the tag, the privacy of the reader holder is very important. Recently, in order to solve these problems, a number of RFID tag search schemes have been proposed. However, since these schemes did not consider the privacy of reader holders, there are serious privacy breaches of reader holders. In this paper, we propose efficient RFID tag search protocol for passive tags. Our proposed scheme preserves the privacy of reader holders.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.621-635
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• 2012

Although most proposed security schemes have scrutinized their own security models for protecting different types of threats and attacks, this naturally causes a problem as follows-- if a security analysis tool would fit a certain scheme, it may not be proper to other schemes. In order to address this problem, this paper analyzes how security requirements of each paper could be different by comparing with two schemes: Agrawal et al.'s scheme OPES (Order Preserving Encryption Scheme) and Zdonik et al.'s FCE (Fast Comparison Encryption). Zdonik et al. have formally disproved the security of Agrawal et al.'s scheme OPES. Thereafter, some scholars have wondered whether the OPES can guarantee its applicability in a real world for its insecurity or not. However, the analysis by Zdonik et al. does not have valid objectivity because they used the security model INFO-CPA-DB for their scheme FCE to analyze Agrawal et al.'s scheme OPES, in spite of the differences between two schemes. In order to analyze any scheme correctly and apply it to a real world properly, the analysis tool should be comprehensively standardized. We re-analyze Zdonik et al.'s analysis for OPES and then propose general formalizations of security and privacy for all of the encrypted retrieval systems. Finally, we recommend the minimum level of security requirements under our formal definitions. Additional considerations should be also supplemented in accordance with the conditions of each system.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.33-42
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• 2022

In this paper, we proposed a deep learning model based on multi-scale dilated convolution feature fusion for the segmentation of black ice region in road image to send black ice warning to drivers in real time. In the proposed multi-scale dilated convolution feature fusion network, different dilated ratio convolutions are connected in parallel in the encoder blocks, and different dilated ratios are used in different resolution feature maps, and multi-layer feature information are fused together. The multi-scale dilated convolution feature fusion improves the performance by diversifying and expending the receptive field of the network and by preserving detailed space information and enhancing the effectiveness of diated convolutions. The performance of the proposed network model was gradually improved with the increase of the number of dilated convolution branch. The mIoU value of the proposed method is 96.46%, which was higher than the existing networks such as U-Net, FCN, PSPNet, ENet, LinkNet. The parameter was 1,858K, which was 6 times smaller than the existing LinkNet model. From the experimental results of Jetson Nano, the FPS of the proposed method was 3.63, which can realize segmentation of black ice field in real time.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.21-34
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• 2024

In medical images such as MRI(Magnetic Resonance Imaging) and CT(Computed Tomography) images, noise removal has a significant impact on the performance of medical imaging systems. Recently, the introduction of deep learning in image processing technology has improved the performance of noise removal methods. However, there is a limit to removing only noise while preserving details in the image domain. In this paper, we propose a wavelet transform-based CNN(Convolutional Neural Network) model, namely the WT-DnCNN(Wavelet Transform-Denoising Convolutional Neural Network) model, to improve noise removal performance. This model first removes noise by dividing the noisy image into frequency bands using wavelet transform, and then applies the existing DnCNN model to the corresponding frequency bands to finally remove noise. In order to evaluate the performance of the WT-DnCNN model proposed in this paper, experiments were conducted on MRI and CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. The performance experiment results show that the WT-DnCNN model is superior to the traditional filter, i.e., the BM3D(Block-Matching and 3D Filtering) filter, as well as the existing deep learning models, DnCNN and CDAE(Convolution Denoising AutoEncoder) model in qualitative comparison, and in quantitative comparison, the PSNR(Peak Signal-to-Noise Ratio) and SSIM(Structural Similarity Index Measure) values were 36~43 and 0.93~0.98 for MRI images and 38~43 and 0.95~0.98 for CT images, respectively. In addition, in the comparison of the execution speed of the models, the DnCNN model was much less than the BM3D model, but it took a long time due to the addition of the wavelet transform in the comparison with the DnCNN model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.52-59
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• 2009

In general, methods based on histogram or a correction of gamma curve are usually utilized to enhance the contrast of captured image in the dark scene. These methods are efficient to enhance the contrast globally, however, they locally induced the low quality of image. Recently, to resolve the problem, the multi-scaled refiner algorithm improving the contrast with locally averaged lightness is proposed. However, estimating the locally averaged lightness, if there is the object with a high saturated color, the color distortion might be induced by the color of object. Thus, in this paper, the dominant chromaticity of image is estimated to correct the locally averaged lightness in multi-scaled retinex algorithm. Because the average chromaticity of image includes the chromaticity of illumination, the dominant chromaticity is estimated with dividing the average chromaticity of image by the estimated chromaticity of illumination from highlight region. In addition, to improve the lower chroma by multi-scaled retinex algorithm generally, the chroma was compensated preserving the hue in the CIELAB color space.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.355-364
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• 2011

In most applications requiring high-confidential images, reversible watermarking is an effective way to ensure the integrity of images. Many watermarking researches which have been adapted to authenticate contents cannot recover the original image after authentication. However, reversible watermarking inserts the watermark signal into digital contents in such a way that the original contents can be restored without any quality loss while preserving visual quality. To detect malicious tampering, this paper presents a new block-based image authentication algorithm using differential histogram-based reversible watermarking. To generate an authentication code, the DCT-based authentication feature from each image block is extracted and combined with user-specific code. Then, the authentication code is embedded into image itself with reversible watermarking. The image can be authenticated by comparing the extracted code and the newly generated code and restored into the original image. Through experiments using multiple images, we prove that the presented algorithm has achieved over 97% authentication rate with high visual quality and complete reversibility.