• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1799-1818
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• 2018

Malware detections continue to be a challenging task as attackers may be aware of the rules used in malware detection mechanisms and constantly generate new breeds of malware to evade the current malware detection mechanisms. Consequently, novel and innovated malware detection techniques need to be investigated to deal with this circumstance. In this paper, we propose a new secure malware detection system in which API call fragments are used to recognize potential malware instances, and these API call fragments together with the homomorphic encryption technique are used to construct a privacy-preserving Naive Bayes classifier (PP-NBC). Experimental results demonstrate that the proposed PP-NBC can successfully classify instances of malware with a hit-rate as high as 94.93%.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.17-24
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• 2018

Today, we are living in the era of data and information. With the advent of Internet of Things (IoT), the popularity of social networking sites, and the development of mobile devices, a large amount of data is being produced in diverse areas. The collection of such data generated in various area is called big data. As the importance of big data grows, there has been a growing need to share big data containing information regarding an individual entity. As big data contains sensitive information about individuals, directly releasing it for public use may violate existing privacy requirements. Thus, privacy-preserving data publishing (PPDP) has been actively studied to share big data containing personal information for public use, while preserving the privacy of the individual. K-anonymity, which is the most popular method in the area of PPDP, transforms each record in a table such that at least k records have the same values for the given quasi-identifier attributes, and thus each record is indistinguishable from other records in the same class. As the size of big data continuously getting larger, there is a growing demand for the method which can efficiently anonymize vast amount of dta. Thus, in this paper, we develop an efficient k-anonymity method by using Spark distributed framework. Experimental results show that, through the developed method, significant gains in processing time can be achieved.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.55-63
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• 1997

Precision digital data capture and spatial analysis system to cultural properties play important roles in preserving the existing properties. This study presents the acquisition oi digital data in geometrical context and spatial analysis for more effective management to cultural properties. Established in the same coordinates system, Precision 3D measurements and image analysis were peformed. In addition, geometrical analysis, and 3D monitoring to Songsanri Royals Tombs in Gongju were carried out in generating basedata for conservation plan.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1271-1278
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• 2000

A general curve and surface is a basic method to generate Free-form object using the fundamental properties of blending function. In typical method, there is an overhead of calculating to present Free-form object with the line segments and interpolation algorithm, In this paper, for resolving this problem efficiently, it will propose the flexible Free-form curves/surfaces using Ball curve shape-preserving property. This method includes Geometric Continuity that is needed to design Free-form Surface of high degree consisted with many curves. Also, when lots of data are reduced using Geometric Property of Free-form curves, the shape-preserving property of resulting object can be maintained, then it can represent any Free-form object with less calculating .

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.87-90
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• 2005

XML(eXtensible Markup Language)은 웹 상의 데이터를 표현하고, 교환하기 위한 표준 언어로써 XML 로 표현된 문서를 관계형 데이터베이스 관리시스템(RDBMS)에 저장하고 관리하는 기법에 대한 연구[1][2][3]가 활발히 진행되어 왔다. 이러한 연구들은 DTD(Document Type Definition)를 입력 받아 해당 DTD 에서 관계형 스키마를 추론하는 기법을 사용한다. 하지만, 기존의 연구들은 DTD 간소화 절차를 적용하기 때문에 DTD 내에서 추론될 수 있는 의미적인 부분들이 스키마 생성 시에 보존이 되지 못한다. 또한, 기존의 연구들은 XML 데이터의 내용(content)와 구조(structure) 정보만을 저장하는데 초점이 맞춰져 있기 때문에, XML 문서 저장 시 데이터의 무결성을 보장하기 위해 저장프로시져나 트리거를 이용해야 하는 번거로움이 생긴다. 본 논문에서는 [3]의 연구에서 제시한 Inlining 기법을 기반으로 기존의 Inlining 기법의 문제점인 DTD 에서 추론할 수 있는 의미적인 부분의 손실을 관계형 스키마로 보존하는 방법과 효율적인 릴레이션 생성을 위해 개선된 Inlining 기법을 제시한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.547-552
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• 1999

In [1], it is shown that a subclass of ETBFs, which are self-dual ETBFs can be expressed as a weighted average of median subfiltered outputs. In this paper, the ETBF is extended for real-valued input. Using this result, the scale-preservation and translation-invariance properties of the ETBFs are investigated. In particular, it is shown that the ETBFs are scale-preserving if and only if it is extended self-dual.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.601-607
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• 2018

Median filtering is a nonlinear method which is known to be effective in removing impulse noise while preserving local image structure relatively well. However, it could still suffer the smearing phenomena of edges and fine details into neighbors due to undesirable influence from the pixels whose values are far off from the true value of the pixel at hand. This drawback mainly comes from the fact that median filters typically employ a regular shape window for collecting the pixels used in the filtering operation. In this paper, we propose a median filtering method which employs an irregular shape filter window in collecting neighboring pixels around the pixel to be denoised. By employing an irregular shape window, we can achieve good noise suppression while preserving image details. Experimental results have shown that our approach is superior to regular window-based methods.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1345-1357
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• 2017

A prototype selection method chooses a small set of training points from a whole set of class data. As the data size increases, the selected prototypes play a significant role in covering class regions and learning a discriminate rule. This paper discusses the methods for selecting prototypes in a classification framework. We formulate a prototype selection problem into a set covering optimization problem in which the sets are composed with distance metric and predefined classes. The formulation of our problem makes us draw attention only to prototypes per class, not considering the other class points. A training point becomes a prototype by checking the number of neighbors and whether it is preselected. In this setting, we propose a greedy algorithm which chooses the most relevant points for preserving the class dominant regions. The proposed method is simple to implement, does not have parameters to adapt, and achieves better or comparable results on both artificial and real-world problems.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.45-50
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• 2019

Recently, character motion have been used extensively in the entertainment business, and researchers have investigated algorithms of reproducing, editing, and simulating mimic human movements. Also, many recent researches have suggested how a character interacts with its surrounding environment in terms of motion. Specially, spatial relationships of the environment have been introduced for adapting and preserving character motion. In this paper, we propose a motion adaptation technique preserving a spatial property between a virtual character and the configuration of its surrounding space. Additionally, we report on experimental results of smoothly adapted motions in various environmental structures with original motions such as walk, jump, and tumbling.