• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.65-72
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• 2020

Today, the Internet of Things is used in many places, including homes, industrial sites, and hospitals, to give us convenience. Many services generate new value through real-time data collection, storage and analysis as devices are connected to the network. Many of these fields are creating services and applications that utilize sensors and communication functions within IoT devices. However, since everything can be hacked, it causes a huge privacy threat to users who provide data. For example, a variety of sensitive information, such as personal information, lifestyle patters and the existence of diseases, will be leaked if data generated by smarwatches are abused. Development of IoT must be accompanied by the development of security. Recently, Differential Privacy(DP) was adopted to privacy-preserving data processing. So we propose the method that can aggregate health data safely on smartwatch platform, based on DP.

• 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 Internet Technology
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• v.22 no.5
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• pp.1069-1082
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• 2021

The Internet of Things (IoT) is vulnerable to a wide range of security risks, which can be effectively mitigated by applying Cyber Threat Intelligence (CTI) sharing as a proactive mitigation approach. In realizing CTI sharing, it is of paramount importance to guarantee end-to-end protection of the shared information as unauthorized disclosure of CTI is disastrous for organizations using IoT. Furthermore, resource-constrained devices should be supported through lightweight operations. Unfortunately, the aforementioned are not satisfied by the Hypertext Transfer Protocol Secure (HTTPS), which state-of-the-art CTI sharing systems mainly depends on. As a promising alternative to HTTPS, Ephemeral Diffie-Hellman over COSE (EDHOC) can be considered because it meets the above requirements. However, EDHOC in its current version contains several security flaws, most notably due to the unprotected initial message. Consequently, we propose a lightweight end-to-end privacy-preserving security protocol that improves the existing draft EDHOC protocol by utilizing previously shared keys and keying materials while providing ticket-based optimized reauthentication. The proposed protocol is not only formally validated through BAN-logic and AVISPA, but also proved to fulfill essential security properties such as mutual authentication, secure key exchange, perfect forward secrecy, anonymity, confidentiality, and integrity. Also, comparing the protocol's performance to that of the EDHOC protocol reveals a substantial improvement with a single roundtrip to allow frequent CTI sharing.

• 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 .

• Annual Conference of KIPS
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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.