• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.167-172
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• 2005

A rapid growth in the number of Internet users and in massive media contents tends to cause server overload and high network traffic. As a consequence, it can be safely assumed that the quality of service is on the brink of deterioration. A solution of this problem is the development of the Content Distribution Network. Therefore, in this paper, we propose a transmission model using CDN. This model uses regional media server which closes to client, and uses MDC coding and multi-channel to reduce packet loss and delay. In conclusion, this study improved performance of multimedia service by reducing packet loss and delay.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.434-441
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• 2001

The concept of network memory was introduced for the efficient exploitation of main memory in a cluster. Network memory can be used to speed up applications that frequently access large amount of disk data. In this paper, we present a memory a management algorithm that does not require prior knowledge of access patterns and that is practical to implement under the web server cluster, In addition, our scheme has a good user response time for various access distributions of web documents. Through a detailed simulation, we evaluate the performance of our memory managment algorithms.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.379-390
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• 2005

Intensive studies have been made in the area of VOD server Multimedia files in the VOD sever are characterized with the large volume of data, the requirements of synchronization and real-time playback of streams. The basic goal of the study is to find an efficient mechanism to allow maximum number of users under the limited resources such as Buffer size and disk bandwidth. we propose a efficient $pre\_fetching$ policy for multimedia services with dynamic monitoring and management of VOD sever resources. Simulation results show that the rate of buffer usage and service time of proposed scheme are about $28\%$ performance improved than that of traditional methods. This implies that our method can allow much more users for given resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2277-2285
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• 2008

Nowadays, in many mobile device environment, while the demand for using web service is increasing, there are many limitations on web-browsing in wireless network because of various restrictions and problems in reality. We need improvement in function of mobile web service engine because we can't be satisfied with the multiple demands by using previous capacity of web server in rapidly changing web environment. Therefore, this paper improves the service environment for web service users by introducing intermediary technology to web service. This paper embodies intermediary based web service framework for improvement of the function of mobile web service and for the interoperability of mobile device and web server.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.110-116
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• 2021

This paper proposed a real-time earlobe detection system using deep learning on the web. Existing deep learning-based detection methods often find independent objects such as cars, mugs, cats, and people. We proposed a way to receive an image through the camera of the user device in a web environment and detect the earlobe on the server. First, we took a picture of the user's face with the user's device camera on the web so that the user's ears were visible. After that, we sent the photographed user's face to the server to find the earlobe. Based on the detected results, we printed an earring model on the user's earlobe on the web. We trained an existing YOLO v5 model using a dataset of about 200 that created a bounding box on the earlobe. We estimated the position of the earlobe through a trained deep learning model. Through this process, we proposed a real-time earlobe detection system on the web. The proposed method showed the performance of detecting earlobes in real-time and loading 3D models from the web in real-time.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.127-136
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• 2021

Real-time human recognition is a challenging task, as the images are captured in an unconstrained environment with different poses, makeups, and styles. This limitation is addressed by generating several facial images with poses, makeup, and styles with a single reference image of a person using Generative Adversarial Networks (GAN). In this paper, we propose deep learning-based human recognition using integration of GAN and Spatial Domain Techniques. A novel concept of human recognition based on face depiction approach by generating several dissimilar face images from single reference face image using Domain Transfer Generative Adversarial Networks (DT-GAN) combined with feature extraction techniques such as Local Binary Pattern (LBP) and Histogram is deliberated. The Euclidean Distance (ED) is used in the matching section for comparison of features to test the performance of the method. A database of millions of people with a single reference face image per person, instead of multiple reference face images, is created and saved on the centralized server, which helps to reduce memory load on the centralized server. It is noticed that the recognition accuracy is 100% for smaller size datasets and a little less accuracy for larger size datasets and also, results are compared with present methods to show the superiority of proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4742-4770
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• 2019

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.153-161
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• 2021

Real-time access is required to handle continuous and unstructured data and should be flexible in management under dynamic state. Platform can be built to allow data collection, storage, and processing from local-server or multi-server. Although the former centralize method is easy to control, it creates an overload problem because it proceeds all the processing in one unit, and the latter distributed method performs parallel processing, so it is fast to respond and can easily scale system capacity, but the design is complex. This paper provides data collection and processing on one platform to derive significant insights from various data held by an enterprise or agency in the latter manner, which is intuitively available on dashboards and utilizes Spark to improve distributed processing performance. All service utilize dockers to distribute and management. The data used in this study was 100% collected from Kafka, showing that when the file size is 4.4 gigabytes, the data processing speed in spark cluster mode is 2 minute 15 seconds, about 3 minutes 19 seconds faster than the local mode.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.5
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• pp.153-164
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• 2004

Under a large-scale client-server service environment, e.g., online games, encrypting data for acquiring information security often causes overload to the server and hence degradation of the service itself. Therefore, for reducing encryption payload, it is necessary to use adequately an efficient encryption scheme with respect to the security requirements of transmission data. In this paper, we propose a packet encryption scheme using multiple cryptosystems to realize such capability, which assigns a different cryptosystem according to the security requirements level. The proposed encryption scheme is applicable to internet services with heavy traffic ratios in which different kinds of data packets are incessantly transmitted between clients and servers. To show its effectiveness and superiority, the performance of the proposed encryption scheme is verified by experiments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.3
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• pp.3-13
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• 2002

There are cases that revoke the certification because of disclosure of private key, deprivation of qualification and the expiration of a term of validity on PKI. So, a user has to confirm the public key whether valid or invalid in the certification. There are many methods such as CRL, Delta-CRL, OCSP for the cert-validation of certification. But these methods have many problems, which cause overload traffic on network and the CRL server because of realtime processing for cert-validation of certification. In this paper we proposed cert-validation of certification improvement method based on FM Subcarrier Broadcasting, which solved problems that are data integrity by different time between transmission and receiving for CRL, and overload traffic on network and the CRL server the realtime management.