• Journal of Information Processing Systems
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• v.13 no.3
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• pp.573-589
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• 2017

Cloud computing is an attractive solution that can provide low cost storage and powerful processing capabilities for government agencies or enterprises of small and medium size. Yet the confidentiality of information should be considered by any organization migrating to cloud, which makes the research on relational database system based on encryption schemes to preserve the integrity and confidentiality of data in cloud be an interesting subject. So far there have been various solutions for realizing SQL queries on encrypted data in cloud without decryption in advance, where generally homomorphic encryption algorithm is applied to support queries with aggregate functions or numerical computation. But the existing homomorphic encryption algorithms cannot encrypt floating-point numbers. So in this paper, we present a mechanism to enable the trusted party to encrypt the floating-points by homomorphic encryption algorithm and partial trusty server to perform summation on their ciphertexts without revealing the data itself. In the first step, we encode floating-point numbers to hide the decimal points and the positive or negative signs. Then, the codes of floating-point numbers are encrypted by homomorphic encryption algorithm and stored as sequences in cloud. Finally, we use the data structure of DoubleListTree to implement the aggregate function of SUM and later do some extra processes to accomplish the summation.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.11
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• pp.71-81
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• 1999

In this paper, digital holographic data storage system is implemented to record and retrieve the color images using new direct access method and binary image processing. As a result of applying image processing via a proposed direct access method, we can reduce the number of data page than binary image processing using raw file and replay color image of resolution of $128{\times}80{\times}256$ (6.6KB). Also it is showed that the input data can be transformed into digital holograms regardless of any kinds of file such as character data, moving picture. etc.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.424-427
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• 2015

근래 들어 모바일 기기의 시스템을 장악하여 사용자의 기밀 정보를 빼내는 악성 행위의 한 방법으로 Code Reuse Attack (CRA)이 널리 사용되고 있다. 이와 같은 CRA를 막기 위하여 call-return이 일어날 때마다 이들 address를 비교해 보는 shadow stack과 branch에 대한 몇 가지 규칙을 두어 CRA 를 탐지하는 branch regulation과 같은 방식이 연구되었다. 우리는 shadow stack과 branch regulation을 종합하여 여러 종류의 CRA를 적은 성능 오버헤드로 탐지할 수 있는 CRA Detection System을 만들고자 한다. 이를 위하여 반드시 선행 되어야 할 연구인 바이너리 파일 분석과 meta-data 생성 및 압축 기술을 제안한다. 실험 결과 생성된 meta-data는 압축 기술을 적용하기 전보다 1/2에서 1/3 가량으로 그 크기가 줄어들었으며 CRA Detection System의 탐지가 정상적으로 동작하는 것 또한 확인할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.369-372
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• 2018

최근 지식경영에 있어 특허를 통한 지식재산권 확보는 기업 운영에 큰 영향을 주는 요소이다. 성공적인 특허 확보를 위해서, 먼저 변화하는 특허 분류 제계를 이해하고, 방대한 특허 정보 데이터를 빠르고 신속하게 특허 분류 체계에 따라 분류화 시킬 필요가 있다. 본 연구에서는 머신 러닝 기술 중에서도 계층적 주의 네트워크를 활용하여 특허 자료의 초록을 학습시켜 분류를 할 수 있는 방법을 제안한다. 그리고 본 연구에서는 제안된 계층적 주의 네트워크의 성능을 검증하기 위해 수정된 입력데이터와 다른 워드 임베딩을 활용하여 진행하였다. 이를 통하여 특허 문서 분류에 활용하려는 계층적 주의 네트워크의 성능과 특허 문서 분류 활용화 방안을 보여주고자 한다. 본 연구의 결과는 많은 기업 지식경영에서 실용적으로 활용할 수 있도록 지식경영 연구자, 기업의 관리자 및 실무자에게 유용한 특허분류기법에 관한 이론적 실무적 활용 방안을 제시한다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.110-113
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• 2003

In this paper, the multi-channel high speed data acquisition system is implemented. This high speed signal processing system for 3-D image display is applicable to the manipulation of a medical image processing, multimedia data and various fields of digital image processing. In order to convert the analog signal into digital one, A/D conversion circuit is designed. PCI interface method is designed and implemented, which is capable of transmission a large amount of data to computer. In order to, especially, channel extendibility of images acquisition, bus communication method is selected. By using this bus method, we can interface each module effectively. In this paper, 32-channel A/D conversion and PCI interface system for 3-dimensional and real-time display of the retina image is developed. The 32-channel image acquisition system and high speed data transmission system developed in this paper is applicable to not only medical image processing as 3-D representation of retina image but also various fields of industrial image processing in which the multi-point realtime image acquisition system is needed.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.630-644
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• 2021

Educational data analysis is attracting increasing attention with the rise of the big data industry. The amounts and types of learning data available are increasing steadily, and the information technology required to analyze these data continues to develop. The early identification of potential dropout students is very important; education is important in terms of social movement and social achievement. Here, we analyze educational data and generate predictive models for student dropout using logistic regression, a decision tree, a naïve Bayes method, and a multilayer perceptron. The multilayer perceptron model using independent variables selected via the variance analysis showed better performance than the other models. In addition, we experimentally found that not only grades but also extracurricular activities were important in terms of preventing student dropout.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1082-1084
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• 2011

최근 스마트폰의 보급률이 급격하게 증가함에 따라 스마트폰 사용자들이 요구하는 어플리케이션들도 더욱 다양해지고 어플리케이션들의 효율성 또한 높아져야하는 상황이다. 또한 대부분의 스마트폰 어플리케이션들이 데이터를 효율적으로 저장, 관리하기 위해서 DataBase를 이용하고 있다. 비록 하드웨어기술이 눈부시게 발전하기는 했지만, 아직까지는 제한적인 스마트폰 기기의 하드웨어 환경상 효율적인 어플리케이션을 개발하기 위해서는 DataBase를 효율적으로 설계하고 각종 쿼리문을 적절하게 활용하여 최적의 성능을 제공할 수 있도록 구현되어야 한다. 따라서 본 연구는 변경사항이 적은 Data는 SQLite를 이용하여 스마트폰 어플리케이션 내부의 DataBase에 저장하고, 변동이 잦은 Data는 별도의 Server DataBase를 이용하여 스마트폰과의 네트워크 통신을 이용한 연동을 통해 어플리케이션의 내용이 업데이트 되도록 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.2-4
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• 2023

Sequence data plays an important role in the field of intelligence, especially for industrial control, traffic control and other aspects. Finding abnormal parts in sequence data has long been an application field of AI technology. In this paper, we propose an anomaly detection method for sequence data using a diffusion model. The diffusion model has two major advantages: interpretability derived from rigorous mathematical derivation and unrestricted selection of backbone models. This method uses the diffusion model to predict and reconstruct the sequence data, and then detects the abnormal part by comparing with the real data. This paper successfully verifies the feasibility of the diffusion model in the field of anomaly detection. We use the combination of MLP and diffusion model to generate data and compare the generated data with real data to detect anomalous points.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.37-44
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• 2003

One of the characteristics of both on-line analytical processing(OLAP) applications and decision support systems is to provide aggregated source data. The purpose of this study is to discuss on the aggregation of multi-dimensional data. In this paper, we (1) examine the SQL aggregate functions and the GROUP BY operator, (2) introduce the Data Cube and MDX, (3) present an example for the practical usage of the Data Cube and MDX using sample data.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.88-95
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• 2022

Detecting anomalies in human movement is an important task in industrial applications, such as monitoring industrial disasters or accidents and recognizing unauthorized factory intruders. In this paper, we propose an abnormal worker movement detection system based on data stream processing and hierarchical clustering. In the proposed system, Apache Spark is used for streaming the location data of people. A hierarchical clustering-based anomalous trajectory detection algorithm is designed for detecting anomalies in human movement. The algorithm is integrated into Apache Spark for detecting anomalies from location data. Specifically, the location information is streamed to Apache Spark using the message queuing telemetry transport protocol. Then, Apache Spark processes and stores location data in a data frame. When there is a request from a client, the processed data in the data frame is taken and put into the proposed algorithm for detecting anomalies. A real mobility trace of people is used to evaluate the proposed system. The obtained results show that the system has high performance and can be used for a wide range of industrial applications.