• 정보처리학회논문지D
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• 제11D권2호
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• pp.485-494
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• 2004

무선 인터넷 단말기 이용자들은 최근에 휴대폰이나 PDA와 같은 무선 인터넷 단말기를 이용한 고객 관계 관리로, 영업 사원들은 모바일 그룹웨어와 연동해 실시간으로 영업데이터와 고객정보를 알아내고 고객들은 무선으로 제품정보와 매입처 검색, 배송, 주문, 결제까지 편리하게 할 수 있다는 게 이점이다. 이에 본 논문에서는 사용자의 성향, 위치, 구매 정보를 이용해 실시간 맞춤 프로모션 정보를 모바일로 제공하는 서비스를 위해, 무선인터넷단말기의 안전한 데이터 전송을 위한 무선 인터넷 환경의 전환과 암호화 기술의 강조, 그리고 안전하고 신뢰할 수 있는 통신 환경 구축에 있어서 핵심적인 역할을 수행할 WTLS(Wireless Transport Layer Security) 기반의 무선인터넷단말기의 데이터 무결성 보장을 위한 보안 모듈 구현에 대한 방안을 제시한다.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.239-250
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• 2019

An individual's health data is very sensitive and private. Such data are usually stored on a private or community owned cloud, where access is not restricted to the owners of that cloud. Anyone within the cloud can access this data. This data may not be read only and multiple parties can make to it. Thus, any unauthorized modification of health-related data will lead to incorrect diagnosis and mistreatment. However, we cannot restrict semipublic access to this data. Existing security mechanisms in e-health systems are competent in dealing with the issues associated with these systems but only up to a certain extent. The indigenous technologies need to be complemented with current and future technologies. We have put forward a method to complement such technologies by incorporating the concept of blockchain to ensure the integrity of data as well as its provenance.

• 대한기계학회논문집A
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• 제29권5호
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• pp.734-742
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• 2005

The present study proposes the integrity evaluation model for a straight pipe with local wall thinning defect, which reflects the characteristics of training shape and loading condition in the Piping of nuclear power plant. For this purpose, a series of finite element analyses are performed under various defect geometries and loading conditions, and real pipe experiment data performed previously is employed. The model includes the effect of thinning length as well as thinning depth and width, and also it considers the combined loading effect between internal pressure and bending moment. The proposed model has been validated using the results of finite element analysis and pipe experiment data. The results indicate that the proposed model provides more reliable predictions of pipe failure than the current existing model, in terms of accuracy, consistency, and conservativeness of results.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.571-585
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• 2021

Applications for object detection are expanding as it is automated through artificial intelligence-based processing, such as deep learning, on a large volume of images and videos. High dependence on training data and a non-transparent way to find answers are the common characteristics of deep learning. Attacks on training data and training models have emerged, which are closely related to the nature of deep learning. Privacy, integrity, and robustness for the extracted information are important security issues because deep learning enables object recognition in images and videos. This paper summarizes the security issues that need to be addressed for future applications and analyzes the state-of-the-art security studies related to robustness, privacy, and integrity of object detection for images and videos.

• 한국해양공학회지
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• 제15권1호
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• pp.73-78
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• 2001

Soundness evaluation of a structure being constructed under the sea is usually difficult. In this study, a cross-hole sonic logging(CSL) which have been used for non-destructive test of concrete piles is adopted for the integrity test and monitoring of DCM(deep cement mixing) treated soils. Chemical and physical characteristics of raw ground materials are analysed to delineate ground environmental effects on the strength of DCM treated soils. In order to convert cross-hole sonic logging data into compressive strength, correlations between compressive strengths and wave velocities of core samples have been obtained. It is found that there is little effect of ground environment on the strength of the DCM treated soils, and the density distribution of core samples and cross-hole logging data show that a defective zone may exist in the DCM treated soils. With the time lapse, however, the defective zone has been cured and consequently, compressive strength of the DCM treated soils increases and satisfies the design parameter. From this study it can be concluded that the cross-hole sonic logging can be used for the integrity test as well as monitoring the curing stage of the structures, successfully.

• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.317-325
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• 2022

In this paper, we developed a single frequency-based RRAIM to monitor integrity of the UAM landing vertically in urban area with only low-cost single-frequency GPS receiver. Conventional dual-frequency RRAIM eliminates ionospheric delay through a combination of frequencies. In this study, ionospheric delay was directly modeled. Drift error of residual ionospheric delay is modeled using the previously studied result on ionospheric rates of change. To verify the performance of the proposed RRAIM algorithm, a simulation of vertical landing UAM in urban area was conducted. It was assumed that the protection level at the initial position was calculated through SBAS correction data. During vertical landing, integrity monitored by receiver alone without external correction data. In the 60 sec simulation, the protection level of the proposed RRAIM compared to the conventional RRAIM was calculated to be 140% due to the accumulated ionospheric delay error. Nevertheless, it was confirmed that the final vertical protection level meeting the requirements of LPV-200, which cannot be achieved with single frequency GPS receiver alone.

• 융합신호처리학회논문지
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• 제18권2호
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• pp.55-61
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• 2017

전파천문분야에서 관측데이터의 저장을 위해 대용량 HDD를 RAID로 연결한 디스크 팩을 활용하고 있다. VLBI 관측의 경우 관측속도가 빨라지고 광대역으로 확장되면서 많은 양의 관측데이터를 저장해야 한다. HDD는 사용회수가 많아질수록 고장이 많이 발생하고 있으며, 이것을 찾아서 복구하는데 많은 시간이 소요된다. 또한 고장난 HDD를 계속 사용할 경우 관측데이터의 손실이 발생한다. 그리고 새 HDD를 구입하여 많은 비용도 필요하게 된다. 본 연구에서는 FirmOS를 이용하여 SATA HDD의 무결성 검사 시스템을 개발하였다. FirmOS는 일반 서버보드와 CPU를 갖는 시스템에서 특정목적에만 동작하도록 개발한 OS이다. 개발한 시스템은 FirmOS 기반에서 SATA HDD의 물리적인 영역에 특정 패턴의 데이터를 쓰고 읽는 과정을 수행한다. 그리고 HDD 제어기의 메모리 영역에서 HDD로부터 읽어들인 저장된 패턴 데이터와 비교를 수행하는 방식으로 HDD의 무결성 검사를 확인하는 방법을 채용하였다. 개발한 시스템을 활용하여 VLBI 관측에서 활용하고 있는 디스크 팩의 고장여부를 쉽게 확인할 수 있었으며, 관측효율을 향상시킬 수 있는데 많은 도움이 되고 있다. 본 논문에서는 개발한 SATA HDD 무결성 확인 시스템의 설계, 구성, 시험 등에 대해 자세히 기술한다.

• 한국BIM학회 논문집
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• 제9권4호
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• pp.31-40
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• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.504-519
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• 2023

Heart disease is becoming the top reason of death all around the world. Diagnosing cardiac illness is a difficult endeavor that necessitates both expertise and extensive knowledge. Machine learning (ML) is becoming gradually more important in the medical field. Most of the works have concentrated on the prediction of cardiac disease, however the precision of the results is minimal, and data integrity is uncertain. To solve these difficulties, this research creates an Integrated Accurate-Secure Heart Disease Prediction (IAS) Model based on Deep Convolutional Neural Networks. Heart-related medical data is collected and pre-processed. Secondly, feature extraction is processed with two factors, from signals and acquired data, which are further trained for classification. The Deep Convolutional Neural Networks (DCNN) is used to categorize received sensor data as normal or abnormal. Furthermore, the results are safeguarded by implementing an integrity validation mechanism based on the hash algorithm. The system's performance is evaluated by comparing the proposed to existing models. The results explain that the proposed model-based cardiac disease diagnosis model surpasses previous techniques. The proposed method demonstrates that it attains accuracy of 98.5 % for the maximum amount of records, which is higher than available classifiers.

• 한국안전학회지
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• 제18권1호
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• pp.8-13
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• 2003

This study proposes integrity evaluation method of weld zone in rails using high precision distance amplitude characteristics curve(DACC) and ultrasonic signals. For these purposes, the ultrasonic signals for defects(porosity and crack) of weld zone in rails are acquired in the type of time series data and echo strength. 6 lines in the DACC indicated damage evaluation standard of weld zone in rails. The aquired ultrasonic signals agree fairly well with the mesured results of reference block and sensitivity block(defect location, beam propagation distance, echo strength, etc). The proposed high precision DACC in this study can be used for integrity evaluation of weld zone in rails.