• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4250-4267
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• 2015

Although many revocable group signature schemes has been proposed in vehicular ad hoc networks (VANETs), the existing schemes suffer from long computation delay on revocation that they cannot adapt to the dynamic VANETs. Based on Chinese remainder theorem and Schnorr signature algorithm, this paper proposes an efficient revocable group signature scheme in VANETs. In the proposed scheme, it only need to update the corresponding group public key when a member quits the group, and in the meanwhile the key pairs of unchanged group members are not influenced. Furthermore, this scheme can achieve privacy protection by making use of blind certificates. Before joining to the VANETs, users register at local trusted agencies (LTAs) with their ID cards to obtain blind certificates. The blind certificate will be submitted to road-side units (RSUs) to verify the legality of users. Thus, the real identities of users can be protected. In addition, if there is a dispute, users can combine to submit open applications to RSUs against a disputed member. And LTAs can determine the real identity of the disputed member. Moreover, since the key pairs employed by a user are different in different groups, attackers are not able to track the movement of users with the obtained public keys in a group. Furthermore, performance analysis shows that proposed scheme has less computation cost than existing schemes.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.22-28
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• 2017

The Convolutional Neural Network(CNN) can be divided into two stages: feature extraction and classification. The hyperparameters such as kernel size, number of channels, and stride in the feature extraction step affect the overall performance of CNN as well as determining the structure of CNN. In this paper, we propose a method to optimize the hyperparameter in CNN feature extraction stage using Parameter-Setting-Free Harmony Search (PSF-HS) algorithm. After setting the overall structure of CNN, hyperparameter was set as a variable and the hyperparameter was optimized by applying PSF-HS algorithm. The simulation was conducted using MATLAB, and CNN learned and tested using mnist data. We update the parameters for a total of 500 times, and it is confirmed that the structure with the highest accuracy among the CNN structures obtained by the proposed method classifies the mnist data with an accuracy of 99.28%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1764-1770
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• 2007

The binding update of MIPv6 which basically makes a route optimization lets MN bring about high signaling traffic, packet loss and delay. HMIPv6, which introduces the MAP protocol, makes the signaling traffic low, thereby reducing the packet losses and delay. However, it still has the same problem in MIPv6 in the case of macro mobility. This paper proposes HMIPv6 with the address insurance policy. It makes MAP prepare LCoA and RCoA before the macro handover happens. When it happens, MN is able to use them after the registration is done in the foreign network. The perormance can be improved because MAP is composed to assure the address in advance. In addition the MAP sends the BU message during the handover, thereby making the proposed scheme better. The simulation shows that the proposed scheme is about 33% shorter than HMIPv6 in the handover delay and about 22% less than FMIPv6 in the packet loss.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.876-879
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• 2009

As performance and feature set of mobile devices are getting better, the scope of things for which they can be used is also getting widened. More than simply browsing information using mobile web, now these devices can interact with users. It requires various features to manage a web site; supporting full-browsing alone is not enough since there are problems such as processing speed, user interface restriction. However, using mobile devices to manage a web site has its own merits since the can be used without restriction of time and location. In this paper, we introduce a mobile web site administration software that provides both online and offline features. It supports CRUD (Create, Read, Update, Delete) operations for news and users. These operations can be executed both offline and online. A user can do most of things offline; It connects to online only when it's absolutely necessary and does those in batch mode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1502-1522
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• 2019

Leakage of secret keys may be the most devastating problem in public key cryptosystems because it means that all security guarantees are missing. The forward security mechanism allows users to update secret keys frequently without updating public keys. Meanwhile, it ensures that an attacker is unable to derive a user's secret keys for any past time, even if it compromises the user's current secret key. Therefore, it offers an effective cryptographic approach to address the private key leakage problem. As an extension of the forward security mechanism in certificate-based public key cryptography, forward-secure certificate-based signature (FS-CBS) has many appealing merits, such as no key escrow, no secure channel and implicit authentication. Until now, there is only one FS-CBS scheme that does not employ the random oracles. Unfortunately, our cryptanalysis indicates that the scheme is subject to the security vulnerability due to the existential forgery attack from the malicious CA. Our attack demonstrates that a CA can destroy its existential unforgeability by implanting trapdoors in system parameters without knowing the target user's secret key. Therefore, it is fair to say that to design a FS-CBS scheme secure against malicious CAs without lying random oracles is still an unsolved issue. To address this problem, we put forward an enhanced FS-CBS scheme without random oracles. Our FS-CBS scheme not only fixes the security weakness in the original scheme, but also significantly optimizes the scheme efficiency. In the standard model, we formally prove its security under the complexity assumption of the square computational Diffie-Hellman problem. In addition, the comparison with the original FS-CBS scheme shows that our scheme offers stronger security guarantee and enjoys better performance.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1239-1249
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• 2018

Optical remote sensing sensors provide visually more familiar images than radar images. However, it is difficult to discriminate sea ice types in optical images using spectral information based machine learning algorithms. This study addresses two topics. First, we propose a semantic segmentation which is a part of the state-of-the-art deep learning algorithms to identify ice types by learning hierarchical and spatial features of sea ice. Second, we propose a new approach by combining of semi-supervised and active learning to obtain accurate and meaningful labels from unlabeled or unseen images to improve the performance of supervised classification for multiple images. Therefore, we successfully added new labels from unlabeled data to automatically update the semantic segmentation model. This should be noted that an operational system to generate ice type products from optical remote sensing data may be possible in the near future.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.158-165
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• 2019

The existing web page was downloaded and provided to the user every time the user requested the page. Therefore, if the same page is repeatedly requested by the user, only the download for the same resource is repeated. This is a factor that causes unnecessary consumption of data. We focus on reducing data consumption caused by unnecessary requests between users and servers, and improving content delivery speed. Therefore, in this paper, we propose a caching system and an algorithm that can reduce the data consumption while maintaining the latest cache by comparing the hash value using the hash function that can detect the change of the file requested by the user.

• Journal of the Korea Computer Graphics Society
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• v.25 no.2
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• pp.11-18
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• 2019

In this paper, we propose a framework that can perform acceleration collision detection efficiently by using a cone based collision area in a particle-based system which requires collision detection with many objects. Three conditions determine particle and cone-based collision regions: 1) If there is a cone position within the radius of the adjacent particle, 2) In the case where the position of the adjacent particle exists in the cone area, 3) When adjacent particles exist between two vectors forming a cone area. As a result, it is defined that when the above conditions are all satisfied, the particle and the region of a cone have collided. In this paper, we automatically update the area of the cone, which is the collision detection area, according to the particle movement. Determine the direction and length of the cone based on the position and velocity of the particle to calculate the dynamic change of the cone. Collision detection is performed quickly using only the particles in the finally calculated area. The acceleration method proposed in this paper is simple to implement because it is executed with a closed form equation instead of explicitly creating the tree data structure, and collision inspection performance is improved in all results.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.417-425
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• 2019

Storage snapshot technology allows to preserve data at a specific point in time, and recover and access data at a desired point in time. It is an essential technology for storage protection application. Existing snapshot methods have some problems in that they dependent on storage hardware vendor, file system or virtual block device. In this paper, we propose a new snapshot method for solving the problems and creating snapshots on-line. The proposed snapshot method uses a method of extracting the log records of update operations at the virtual file system layer to enable the snapshot method to operate independently on file systems, virtual block devices, and storage hardwares. In addition, the proposed snapshot mehod creates and manages snapshots for directories and files without interruption to the storage service. Finally, through experiments we measure the snapshot creation time and the performance degradation caused by the snapshot.