• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.76-78
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• 2014

Naive Bayes (NB, for shortly) learning is more popular, faster and effective supervised learning method to handle the labeled datasets especially in which have some noises, NB learning also has well performance. However, the conditional independent assumption of NB learning imposes some restriction on the property of handling data of real world. Some researchers proposed lots of methods to relax NB assumption, those methods also include attribute weighting, kernel density estimating. In this paper, we propose a novel approach called NB Based on Attribute Weighting in Kernel Density Estimation (NBAWKDE) to improve the NB learning classification ability via combining kernel density estimation and attribute weighting.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.187-197
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• 2010

The fusion stream of recent broadcasting and communication make multimedia content served in the area of broadcasting into IPTV service which transmits it through high-speed internet, cable TV net and satellite net in realtime. However, as the digital broadcasting service is extended to various media, the security of IPTV service content provided to users by service provider is not fully supported by CAS(Conditional Access System) provided by existing broadcasting system. This paper proposes interactive certification protocol which can efficiently distinguish the receiving-qualification of user between Set-Top Box and Smart Card which are parts of configurations for IPTV system. The proposed protocol uses hash function to make Set-Top Box transmit receiving-qualification about the channel fee which user pays more properly than existing protocol. Also, the proposed protocol uses session key generated between receiver and smart card through inter certification process and encrypts EMM not the service to be used by anyone illegally.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6121-6144
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• 2019

Numerous privacy-preserving authentication schemes have been proposed but vehicular ad hoc networks (VANETs) still suffer from security and privacy issues as well as computation and communication overheads. In this paper, we proposed a robust conditional privacy-preserving authentication scheme based on pseudonym root with cuckoo filter to meet security and privacy requirements and reduce computation and communication overheads. In our proposed scheme, we used a new idea to generate pseudonyms for vehicles where each on-board unit (OBU) saves one pseudonym, named as "pseudonym root," and generates all pseudonyms from the same pseudonym. Therefore, OBU does not need to enlarge its storage. In addition, the scheme does not use bilinear pairing operation that causes computation overhead and has no certification revocation list that leads to computation and communication overheads. The proposed scheme has lightweight mutual authentication among all parties and just for once. Moreover, it provides strong anonymity to preserve privacy and resists ordinary attacks. We analyzed our proposed scheme and showed that it meets security and privacy requirements of VANETs and is more efficient than traditional schemes. The communication and computation overheads were also discussed to show the cost-effectiveness of the proposed scheme.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.1
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• pp.41-50
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• 2010

This paper proposes a mutual identification and session key exchange scheme in secure vehicular communication based on the group signature. In VANETs, security requirements such as authentication, conditional privacy, non-repudiation, and confidentiality are required to satisfy various vehicular applications. However, existing VANET security methods based on the group signature do not support a mutual identification and session key exchange for data confidentiality. The proposed scheme allows only one credential to authenticate ephemeral Diffie-Hellman parameters generated every key exchange session. Our scheme provides a robust key exchange and reduces storage and communication overhead. The proposed scheme also satisfies security requirements for various application services in VANETs.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.53-65
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• 2010

Conditional Access System (CAS) is a core security mechanism of IPTV SCP (Service and Content Protection) which enables only authenticated user to be able to watch the broadcasting contents. In the past, it was general that CAS was built in Set-Top Box (STB) as hardware or as a detachable cable card. However, numerous researches in Downloadable CAS (DCAS), where users can download CAS code in their STB through their network, have been recently conducted widely due to the lack of security and scalability problem. In this paper, the security requirements of OpenCable based DCAS which is typical example of downloadable IPTV SCP will be derived, the novel authentication and key management scheme will be proposed by using the Authentication Proxy (AP) which is the core DCAS. Also, the benefits of the proposed system will be evaluated by comparison and analysis with preceding research.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.727-729
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• 2005

나이브베이즈분류기($na\ddot{i}ve$ Bayes classifier)는 학습, 적용 및 계산자원 이용의 측면에서 매우 효율적인 모델이다. 또한, 그 분류 성능 역시 다른 기법에 비해 크게 떨어지지 않음이 다양한 실험을 통해 보여져 왔다. 특히, 데이터를 생성한 실제 확률분포를 나이브베이즈분류기가 정확하게 표현할 수 있는 경우에는 최대의 효과를 볼 수 있다. 하지만, 실제 확률분포에 존재하는 조건부독립성(conditional independence)이 나이브베이즈분류기의 구조와 일치하지 않는 경우에는 성능이 하락할 수 있다. 보다 구체적으로, 각 자질변수(feature variable)들 사이에 확률적 의존관계(probabilistic dependency)가 존재하는 경우 성능 하락은 심화된다. 본 논문에서는 이러한 나이브베이즈분류기의 약점을 효율적으로 해결할 수 있는 자질변수의 통합기법을 제시한다. 자질변수의 통합은 각 변수들 사이의 관계를 명시적으로 표현해 주는 방법이며, 특히 상호정보량(mutual information)에 기반한 통합 변수의 선정이 성능 향상에 크게 기여함을 실험을 통해 보인다.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.41-47
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• 2012

Various Korean word sense disambiguation methods have been proposed using small scale of sense-tagged corpra and dictionary definitions to calculate entropy information, conditional probability, mutual information and etc. for each method. This paper proposes a method using Korean Word Space model which builds word vectors from a large scale of sense-tagged corpus and disambiguates word senses with the similarity calculation between the word vectors. Experiment with Sejong morph sense-tagged corpus showed 94% precision for 200 sentences(583 word types), which is much superior to the other known methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.175-196
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• 2022

Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.