• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1574-1580
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• 2020

Traditional pose estimation methods include using special devices or images through image processing. The disadvantage of using a device is that the environment in which the device can be used is limited and costly. The use of cameras and image processing has the advantage of reducing environmental constraints and costs, but the performance is lower. CNN(Convolutional Neural Networks) were studied for pose estimation just using only camera without these disadvantage. Various techniques were proposed to increase cognitive performance. In this paper, the effect of the skip connection on the network was experimented by using various skip connections on the joint recognition of the hand. Experiments have confirmed that the presence of additional skip connections other than the basic skip connections has a better effect on performance, but the network with downward skip connections is the best performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.5
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• pp.39-48
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• 2003

AAA(Authentication, Authorization, Accounting) protocol is a framework that propose functions of AAA on multiple networks and platforms. AAA protocol is extending from previous RADIUS protocol to Diameter protocol. There are some Diameter applications for variety purpose. Diameter CMS Application makes Diameter messages more secure by using PKI. Diameter CMS Application establish DSA(Diameter Security Association) for end to end security. However the Application has some problems to establish DSA(Diameter Security Association), which can make Diameter system unstable. If one system lose DSA information for some system error - for example, reboot -, the secure communication between two nodes may not be possible. At the application such as MIP, even user registration can't be done. In this paper, we propose a mechannism for DSA re-establishment, and also show the result of the implementation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.105-118
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• 2009

In modern society, as the rapid development of IT technology combined with the computer-based high-speed communication networks makes it possible to provide a wide spectrum of services and devices, we have been confronting a new cultural transformation era, referred to as the information society. However, the requirements to be considered in security aspect have became more complicated and diversified, and there remains the same security weaknesses as in the existing media or protocol. Particularly, the office network device with roaming is susceptible to the different kinds of attacks such as terminal hacking, virus attacks, and information leakage because the computing capacity is relatively low and the loading of already developed security functions is difficult. Although developed as one solution to this problems, PKI security authentication technology isn't suitable for multi-domain environments providing uonments proffice network service, and so the development of a novel authentication system is needed. Therefore, in this paper researched the roaming and device authentication/auth for multitechnology using an ID-based public key, authorization ticket, and Sub-device ticket with a purpose to contribute to the development of the secured and efficient technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1293-1300
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• 2012

With the rapid evolution of mobile devices and the development of wireless networks, users of mobile social network service on smartphone have been increasing. Also the security of personal information as a result of real-time communication and information-sharing are becoming a serious social issue. In this paper, a framework that can be linked with a social network services platform is designed using OpenAPI. In addition, we propose an authentication and detection mechanism to enhance the level of personal information security. The authentication scheme is based on an user ID and password, while the detection scheme analyzes user-designated input patterns to verify in advance whether personal information protection guidelines are met, enhancing the level of personal information security in a social network service environment. The effectiveness and validity of this study were confirmed through performance evaluations at the end.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.1
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• pp.51-61
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• 2010

Koinonia system is designed to fully utilize the advantage of Binary CDMA so as to guarantee QoS in wireless networks. In this paper, we propose the new network structure based on this system and refer to it as BLAN(Binary CDMA LAN). Although BLAN is similar structure to IEEE 802.11 WLAN, it will ensure the fast handover and QoS. We also propose the AKA(Authentication and Key Agreement) protocol and Reauthentication protocol to be used for communication in BLAN. These protocols are securely and efficiently designed using the user identity module to support the more powerful authentication. Hence, BLAN, including the proposed protocols, will support the high mobility and security. In conclusion, we expect that BLAN can be applied to future infrastructure on special environment, and it can be helpful showing the new network model which alternate WLAN.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.29-39
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• 2009

In order to respond against worms which are malicious programs automatically spreading across communication networks, worm detection approach by generating signatures resulting from analyzing worm-related packets is being mostly used. However, to avoid such signature-based detection techniques, usage of exploits employing mutated polymorphic types are becoming more prevalent. In this paper, we propose a novel static analysis approach for detecting the decryption routine of polymorphic exploit code, Our approach detects a code routine for performing the decryption of the encrypted original code which are contained with the polymorphic exploit code within the network flows. The experiment results show that our approach can detect polymorphic exploit codes in which the static analysis resistant techniques are used. It is also revealed that our approach is more efficient than the emulation-based approach in the processing performance.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.211-216
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• 2021

Information from various heterogeneous devices is steadily increasing in distributed cloud environments. This is because high-speed network speeds and high-capacity multimedia data are being used. However, research is still underway on how to minimize information errors in big data sent and received by heterogeneous devices. In this paper, we propose a deep learning-based asymmetric storage management technique for minimizing bandwidth and data errors in networks generated by information sent and received in cloud environments. The proposed technique applies deep learning techniques to optimize the load balance after asymmetric hash of the big data information generated by each device. The proposed technique is characterized by allowing errors in big data collected from each device, while also ensuring the connectivity of big data by grouping big data into groups of clusters of dogs. In particular, the proposed technique minimizes information errors when storing and managing big data asymmetrically because it used a loss function that extracted similar values between big data as seeds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.27-35
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• 2021

This paper proposes a method to mitigate the Catastrophic Forgetting phenomenon in which artificial neural networks forget information on previous data. This method adjusts the Regularization strength by measuring the relationship between previous data and present data. MNIST and EMNIST data were used for performance evaluation and experimented in three scenarios. The experiment results showed a 0.1~3% improvement in the accuracy of the previous task for the same domain data and a 10~13% improvement in the accuracy of the previous task for different domain data. When continuously learning data with various domains, the accuracy of all previous tasks achieved more than 50% and the average accuracy improved by about 7%. This result shows that neural network learning can be properly performed in a CL environment in which data of different domains are successively entered by the method of this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.44-49
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• 2021

Recently, due to COVID-19, studies have been popularly worked to apply neural network to mask wearing automatic detection system. For applying neural networks, the 1-stage detection or 2-stage detection methods are used, and if data are not sufficiently collected, the pretrained neural network models are studied by applying fine-tuning techniques. In this paper, the system is consisted of 2-stage detection method that contain MTCNN model for face recognition and ResNet model for mask detection. The mask detector was experimented by applying five ResNet models to improve accuracy and fps in various environments. Training data used 17,217 images that collected using web crawler, and for inference, we used 1,913 images and two one-minute videos respectively. The experiment showed a high accuracy of 96.39% for images and 92.98% for video, and the speed of inference for video was 10.78fps.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.179-185
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• 2020

Recently, in order to improve the performance of the Earthquake Early Warning System (EEWS) and to supplement the effects of earthquake disaster prevention in epicenters or near epicenters, development of on-site EEWS has been attempted. Unlike the national EEWS, which is used for earthquake disaster prevention by using seismic observation networks for earthquake research and observation, on-site EEWS aims at earthquake disaster prevention and therefore requires efficient design and evaluation in terms of performance and cost. At present, Korea lacks the necessary core technologies and operational know-how, including the use of existing EEWS design criteria and evaluation methods for the development of On-Site EEWS as well as EEWS. This study proposes hardware and software design directions and performance evaluation items and methods for seismic data collection, data processing, and analysis for localization of On-Site EEWS based on the seismic accelerometer requirements of the Seismic and Volcanic Disaster Response Act.