• KIPS Transactions on Computer and Communication Systems
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• v.3 no.11
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• pp.393-402
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• 2014

We have experienced an explosive increase of the IoT(Internet of Things) technology based devices including smart phones and the wireless communications. Also the growing power consumption in IEEE 802.11 WLANs(Wireless LANs) driven by these dramatic increases in not only mobile users and but also wireless APs(Access Points). To reduce the power consumption, this paper proposes a wireless AP power saving algorithm, which minimizes the transmission power without decrease the transmission and carrier sense ranges. A wireless AP which is use in our algorithm checks its own original coverage periodically for whether there is a new STA(Station) or not when its transmission power is decreased. Moreover, if there are no signaling message to connect the wireless AP, it changes its operation mode Wake-up to sleep. A Result shows that the proposed AP algorithm can reduce the total power consumption of the wireless AP approximated 18% and 35% compared to the conventional wireless AP with and without the existing power saving algorithm, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.140-142
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• 2021

Mobile communication technology after 5th generation requires high speed, hyper-connection, and low latency communication. In order to meet technical requirements for secure hyper-connectivity, low-spec IoT devices that are considered the end of IoT services must also be able to provide the same level of security as high-spec servers. For the purpose of performing these security functions, it is required for cryptographic keys to have the necessary degree of stability in cryptographic algorithms. Cryptographic keys are usually generated from cryptographic random number generators. At this time, good noise sources are needed to generate random numbers, and hardware random number generators such as TRNG are used because it is difficult for the low-spec device environment to obtain sufficient noise sources. In this paper we used the chip which is based on quantum characteristics where the decay of radioactive isotopes is unpredictable, and we presented a variety of methods (TRNG) obtaining an entropy source in the form of binary-bit series. In addition, we conducted the NIST SP 800-90B test for the entropy of output values generated by each TRNG to compare the amount of entropy with each method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2848-2869
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• 2017

Mobile Wireless Sensor Networks (MWSN) are usually constrained in energy supply, which makes energy efficiency a key factor to extend the network lifetime. The management of the network topology has been widely used as a mechanism to enhance the lifetime of wireless sensor networks (WSN), and this work presents an alternative to this. Software Defined Networking (SDN) is a well-known technology in data center applications that separates the data and control planes during the network management. This paper proposes a solution based on SDN that optimizes the energy use in MWSN. The network intelligence is placed in a controller that can be accessed through different controller gateways within a MWSN. This network intelligence runs a Topology Control (TC) mechanism to build a backbone of coordinator nodes. Therefore, nodes only need to perform forwarding tasks, they reduce message retransmissions and CPU usage. This results in an improvement of the network lifetime. The performance of the proposed solution is evaluated and compared with a distributed approach using the OMNeT++ simulation framework. Results show that the network lifetime increases when 2 or more controller gateways are used.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.31-40
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• 2018

With the development of IT technology recently, medical information systems are being constructed in an integrated u-health environment through cloud services, IoT technologies, and mobile applications. These kinds of medical information systems should provide the medical staff with authorities to access patients' medical information for emergency status treatments or therapeutic purposes. Therefore, in the medical information systems, the reliable and prompt authentication processes are necessary to access the biometric information and the medical information of the patients in charge of the medical staff. However, medical information systems are accessing with simple and static user authentication mechanism using only medical ID / PWD in the present system environment. For this reason, in this paper, we suggest a dynamic situation authentication mechanism that provides transparency of medical information access including various authentication factors considering patient's emergency status condition and dynamic situation authentication system supporting it. Our dynamic Situation Authentication is a combination of user authentication and mobile device authentication, which includes various authentication factor attributes such as emergency status, role of medical staff, their working hours, and their working positions and so forth. We designed and implemented a dynamic situation authentication system including emergency status decision, dynamic situation authentication, and authentication support DB construction. Finally, in order to verify the serviceability of the suggested dynamic situation authentication system, the medical staffs download the mobile application from the medical information server to the medical staff's own mobile device together with the dynamic situation authentication process and the permission to access medical information to the patient and showed access to medical information.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.223-232
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• 2015

In this system, mobile devices are not independent, they can communicate with each other, one device's change can affect the whole system or other devices. To achieve the above mentioned A Self-Reconfigurable System of Contents, through discover the device and connect process, to establish the connection between the mobile devices. After user assigns two dimension display type, the user can select content to input the system, contents are portioning and broadcast to devices. The system can self-reconfigure contents rapidly and exactly. This technique supports contents self-reconfiguration for devices remove, addition and position exchange. In this paper, when the user uses the hand contacts device, the device sends a signal to assist the system to detection device's position. The system does not need to get accurate devices moving direction, just according to all changed devices position to judge where the devices destination is. This research develops an application according to this technique, and the real machine tests the application using Android platform. Some communication protocols and mathematical modeling methods are proposed. These methods can also be used in other Internet of Things (IoT) fields, such as Drones Navigation, Smart Home, and Informational City management.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1214-1222
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• 2020

Pervasive augmented reality (AR) technology can be used to efficiently search for the required information regarding products in stores through text augmentation in an Internet of Things (IoT) environment. The evolution of context awareness and image processing technologies are the main driving forces that realize this type of AR service. One of the problems to be addressed in the service is that augmented objects are fixed and cannot be replaced efficiently in real time. To address this problem, a real-time mobile AR framework is proposed. In this framework, an optimal object to be augmented is selected based on object similarity comparison, and the augmented objects are efficiently managed using distributed metadata servers to adapt to the user requirements, in a given situation. To evaluate the feasibility of the proposed framework, a prototype system was implemented, and a qualitative evaluation based on questionnaires was conducted. The experimental results show that the proposed framework provides a better user experience than existing features in smartphones, and through fast AR service, the users are able to conveniently obtain additional information on products or objects.

• Annual Conference of KIPS
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• 2017.11a
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• pp.200-202
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• 2017

To improve the security of OAuth 2.0 access token transportation and satisfy the challenge of resources constraint caused by the bearer token access mechanism of the OAuth 2.0, we proposed an extensional client authentication scheme that is based on the Proof-of-Possession (PoP) token mechanism. By improving the integrity of PoP token, we bind a PoP key of a public/private key pair to the PoP token. The authorization server and the resource server can authenticate the identity of the client by verifying whether the client has the possession of the PoP token. If the client can prove that it has a PoP key that matches the PoP token, then the identity of the client can be authenticated. This experimental evaluation can confirm that this scheme effectively dealing with the issue of client identity authentication and reduce resources consumption.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.399-408
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• 2021

Information security reports four types of basic attacks on information. One of the attacks is named as fabrication. Even though mobile devices and applications are showing its maturity in terms of performance, security and ubiquity, location-based applications still faces challenges of quality of service, privacy, integrity, authentication among mobile devices and hence mobile users associated with the devices. There is always a continued fear as how location information of users or IoT appliances is used by third party LB Service providers. Even adversary or malicious attackers get hold of location information in transit or fraudulently hold this information. In this paper, location information fabrication scenarios are presented after knowing basic model of information attacks. Peer-to-Peer broadcast model of location privacy is proposed. This document contains introduction to fabrication, solutions to such threats, management of fabrication mitigation in collaborative or peer to peer location privacy and its cost analysis. There are various infrastructure components in Location Based Services such as Governance Server, Point of interest POI repository, POI service, End users, Intruders etc. Various algorithms are presented and analyzed for fabrication management, integrity, and authentication. Moreover, anti-fabrication mechanism is devised in the presence of trust. Over cost analysis is done for anti-fabrication management due to nature of various cryptographic combinations.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.200-207
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• 2020

Recently, deep neural networks such as CNN are showing excellent performance in various fields such as image classification, object recognition, visual quality enhancement, etc. However, as the model size and computational complexity of deep learning models for most applications increases, it is hard to apply neural networks to IoT and mobile environments. Therefore, neural network compression algorithms for reducing the model size while keeping the performance have been being studied. In this paper, we apply few compression methods to CNN models and evaluate their performances in the embedded environment. For evaluate the performance, the classification performance and inference time of the original CNN models and the compressed CNN models on the image inputted by the camera are evaluated in the embedded board equipped with QCS605, which is a customized AI chip. In this paper, a few CNN models of MobileNetV2, ResNet50, and VGG-16 are compressed by applying the methods of pruning and matrix decomposition. The experimental results show that the compressed models give not only the model size reduction of 1.3~11.2 times at a classification performance loss of less than 2% compared to the original model, but also the inference time reduction of 1.2~2.21 times, and the memory reduction of 1.2~3.8 times in the embedded board.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.