• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.55-64
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• 2023

The Internet of Things (IoT) is the combination of the internet and various sensing devices. IoT security has increasingly attracted extensive attention. However, significant losses appears due to malicious attacks. Therefore, intrusion detection, which detects malicious attacks and their behaviors in IoT devices plays a crucial role in IoT security. The intrusion detection system, namely IDS should be executed efficiently by conducting classification and efficient feature extraction techniques. To effectively perform Intrusion detection in IoT applications, a novel method based on a Conventional Neural Network (CNN) for classification and an improved Genetic Algorithm (GA) for extraction is proposed and implemented. Existing issues like failing to detect the few attacks from smaller samples are focused, and hence the proposed novel CNN is applied to detect almost all attacks from small to large samples. For that purpose, the feature selection is essential. Thus, the genetic algorithm is improved to identify the best fitness values to perform accurate feature selection. To evaluate the performance, the NSL-KDDCUP dataset is used, and two datasets such as KDDTEST²¹ and KDDTEST⁺ are chosen. The performance and results are compared and analyzed with other existing models. The experimental results show that the proposed algorithm has superior intrusion detection rates to existing models, where the accuracy and true positive rate improve and the false positive rate decrease. In addition, the proposed algorithm indicates better performance on KDDTEST⁺ than KDDTEST²¹ because there are few attacks from minor samples in KDDTEST⁺. Therefore, the results demonstrate that the novel proposed CNN with the improved GA can identify almost every intrusion.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.75-85
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• 2012

In general, cellular network is deployed as distributed network architecture, so network equipment is spread out all over the coverage area. This case causes high cost. Recently, centralized network architecture has been deployable at cellular network since base station was able to be virtualized due to advance in computing power. The centralized network architecture in cellular network adjusts its cell radius dynamically and minimizes power consumption of the network. This paper introduces a new centralized deployment way of cellular network using SDR and cloud computing technology. Then, advantage and feasibility of the new network will be reviewed by implementing this novel network.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.444-444
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• 2004

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.10-23
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• 2009

In this paper we propose a novel mobile terminal software architecture supporting energy efficient handover operation in heterogeneous networks. Since the legacy proposals for L3 handover are mostly dependent on IETF Mobile IP which has some problems in movement detection mechanism and no considerations on nested heterogeneous network environment as a result they make serious overload on networks and terminals by performing unnecessary handover in such network environments. The proposed architecture has terminal-oriented network selection and switching architecture where a mobile terminal periodically monitors network status and selects the optimum network, and reduces energy consumption by making L3 handover of Mobile IP to the finally selected network. The network selection method first picks up some candidate networks by considering a terminal speed and power consumption estimation, and determines the final target handover network among the candidates after evaluating multiple factors including QoS required by a terminal, network status, user preference and terminal battery status. Finally we verify the functionality and performance of the energy efficient vertical handover architecture by means of adopting it into a real mobile terminal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.113-125
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• 2019

This research aims to understand the common psychological features of consumer. And master the direction of the development of the network novels derivation by analysis the TV plays adapted from network novels in China's IP industry. To this end, This research determine to analyzed consumer adoption attitude the Behavior Intention of derivative products. The date were collected from 612 Chinese people, from October 15 to October 22 2018. Statistical analysis were through SPSS 21 after data coding and data cleanings process. This research performed frequency analysis exploratory factor analysis, Independent sample t-test, one-way ANOVA, post-analysis Duncan test, correlation analysis and mass regression analysis. The research results are as follows. Firstly, the characteristics(topicality, empathy and interest) of network novel TV play positively related role in the adoption attitudes(cognitive attitude and emotional attitude) of derivatives commodities. At the same time, identity has a more positively related influence than topicality and interest. Secondly, all the characteristics of network novels consisting of topicality, identity and interest play positive related roles in the behavioral intentions of derivative commodities. Thirdly, emotional attitude plays a more positively related role in purchasing intention and recommendation intention compared with cognitive attitude. It is hoped that the research results can play a fundamental role in the production and development of network novels derivatives.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.337-338
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• 2016

This paper introduces a novel dual Full-Bridge LLC(FBLLC)resonant converter for CC/CV Charge of the Battery for Electric Vehicles. One full-bridge LLC resonant converter operates with a fixed-resonant network and the other operates with a variable-resonant network for CC and CV mode operations. The proposed converter can achieve ZVS for all the primary switches and exhibits a highefficiency characteristics like aconventional single FBLLC resonant converter. In addition, the variable-resonant network helps minimize the switching-frequency variation. The dual structure makes the proposed converter possible to achieve ZVS and nearly ZCS for all the primary switches in CC mode operation. Since the proposed converter can operate at a fixed frequency in CV mode, it can minimize the circulating current and achieve nearly ZCS. A 6.6 kW prototype converter is implemented to verify the validity of proposed converter and the maximum efficiency of 98.3% was achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.651-669
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• 2013

In this paper, we study a novel routing algorithm based on load balancing for multi-channel wireless mesh networks. In order to increase the network capacity and reduce the interference of transmission streams and the communication delay, on the basis of weighted cumulative expected transmission time (WCETT) routing metric this paper proposes an improved routing metric based on load balancing and channel interference (LBI_WCETT), which considers the channel interference, channel diversity, link load and the latency brought by channel switching. Meanwhile, in order to utilize the multi-channel strategy efficiently in wireless mesh networks, a new channel allocation algorithm is proposed. This channel allocation algorithm utilizes the conflict graph model and considers the initial link load estimation and the potential interference of the link to assign a channel for each link in the wireless mesh network. It also utilizes the channel utilization percentage of the virtual link in its interference range as the channel selection standard. Simulation results show that the LBI_WCETT routing metric can help increase the network capacity effectively, reduce the average end to end delay, and improve the network performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.5
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• pp.54-62
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• 2007

We propose a novel authentication protocol for wireless mesh network. The proposed authentication protocol is based on the password scheme for convenience of users. The proposed protocol is evaluated through three analyses. The correctness of the proposed protocol is proved using the GNY analysis. By the security analysis, we show that the proposed protocol is resistant to various attacks. For the performance analysis, we implemented the protocol in Linux operating system based laptop and measured the transmission time. The analytic results show that the proposed protocol provides the secure wireless mesh network without considerable performance degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.287-312
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• 2011

Internet chat programs and instant messaging services are becoming increasingly popular among Internet users. One of the crucial issues with Internet chat is how to manage the corresponding pairs of questions and answers in a sequence of conversations. Although many novel methodologies have been introduced to cope with this problem, most are poor in managing interruptions, organizing turn-taking, and conveying comprehension. The Internet environment is recently evolving into a 3D environment, but the problems with managing chat dialogues with the standard 2D text-based chat have remained. Therefore, we propose a more realistic communication model for chat agents in 3D virtual space in this paper. First, we propose a new method to measure the capacity of communication between chat agents and a novel visualization method to depict the hierarchical structure of chat dialogues. In addition, we are concerned with communication networks for virtual people (avatars) living in virtual worlds. In this paper we consider a microscopic aspect of a social network in a relatively short period of time. Our experiments show that our model is highly effective in a virtual chat environment, and the communication network based on our model greatly facilitates investigation of a very large and complicated communication network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4043-4060
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• 2017

Network Intrusion Detection (NID), an important topic in the field of information security, can be viewed as a pattern recognition problem. The existing pattern recognition methods can achieve a good performance when the number of training samples is large enough. However, modern network attacks are diverse and constantly updated, and the training samples have much smaller size. Furthermore, to improve the learning ability of SVM, the research of kernel functions mainly focus on the selection, construction and improvement of kernel functions. Nonetheless, in practice, there are no theories to solve the problem of the construction of kernel functions perfectly. In this paper, we effectively integrate the advantages of the radial basis function kernel and the polynomial kernel on the notion of the game theory and propose a novel kernel SVM algorithm with game theory for NID, called GTNID-SVM. The basic idea is to exploit the game theory in NID to get a SVM classifier with better learning ability and generalization performance. To the best of our knowledge, GTNID-SVM is the first algorithm that studies ensemble kernel function with game theory in NID. We conduct empirical studies on the DARPA dataset, and the results demonstrate that the proposed approach is feasible and more effective.