• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.211-213
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• 2005

데이터 웨어하우스는 축적된 대량의 데이터를 분석하여 의사결정을 지원하는 시스템이다. 의사결정을 위한 대량의 데이터 분석은 많은 비용을 요구하므로, 질의 처리 성능을 높이고 의사 결정자에게 빠른 응답을 제공하는 효율적인 데이터 큐브 생성 기법이 연구되었다. 기존 기법으로는 Multiway Array 기법과 H-Cubing 기법이 있다. Multiway Array 기법은 다차원 집계 연산에 필요한 모든 데이터를 배열로 저장하는 것으로 데이터의 양이 많아질수록 메모리 사용이 증가한다. H-Cubing 기법은 Hyper-Tree를 기반으로 튜플을 트리로 구축하므로 모든 튜플을 트리로 구축해야 하는 비용이 증가한다. 본 논문에서는 데이터 웨어하우스에서 해쉬 테이블을 이용한 효율적인 데이터 큐브 생성 기법을 제안한다. 제안 기법은 데이터 큐브 생성 시 필드 해쉬 테이블과 레코드 해쉬 테이블을 사용한다. 필드 해쉬 테이블은 저장될 레코드 순서 계산을 위하여 각 필드에 대해 레벨 값을 해쉬 테이블로 관리한다. 레코드 해쉬 테이블은 데이터 큐브 테이블에 저장될 레코드의 순서와 데이터 큐브 테이블에 저장하기 위한 임시 레코드의 위치를 관리한다. 필드 해쉬 테이블을 이용하여 다차원 데이터의 저장될 레코드 순서를 빠르게 찾아 저장함으로서 데이터 큐브의 생성속도가 향상된다. 또한 해쉬 테이블 만을 유지하면 되므로 메모리 사용량이 감소한다. 따라서 해쉬 테이블의 사용으로 데이터의 빠른 검색과 데이터 큐브 생성 요청에 빠른 응답이 가능하다.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.109-116
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• 2021

Since RDF (Resource Description Framework) triples are modeled as graph, we cannot directly adopt existing solutions in relational databases and XML technology. In order to store, index, and query Linked Data more efficiently, we propose a convergence indexing method combined R*-tree and K-dimensional trees. This method uses a hybrid storage system based on HDD (Hard Disk Drive) and SSD (Solid State Drive) devices, and a separated filter and refinement index structure to filter unnecessary data and further refine the immediate result. We perform performance comparisons based on three standard join retrieval algorithms. The experimental results demonstrate that our method has achieved remarkable performance compared to other existing methods such as Quad and Darq.

• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1923-1932
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• 1998

This paper deals with a 2-D objects recognition algorithm. And in this paper, we present an algorithm which can reduce the computation time in model retrieval by means of hashing technique instead of using the binary~tree method. In this paper, we treat an object boundary as a string of structural units and use an attributed string matching algorithm to compute similarity measure between two strings. We select from the privileged strings a privileged string wIth mmimal eccentricity. This privileged string is treated as the reference string. And thell we wllstructed hash table using the distance between privileged string and the reference string as a key value. Once the database of all model strings is built, the recognition proceeds by segmenting the scene into a polygonal approximation. The distance between privileged string extracted from the scene and the reference string is used for model hypothesis rerieval from the table. As a result of the computer simulation, the proposed method can recognize objects only computing, the distance 2-3tiems, while previous method should compute the distance 8-10 times for model retrieval.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.1-11
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• 2020

As an important basic building block of the smart grid environment, smart meter provides real-time electricity consumption information to the utility. However, ensuring information security and privacy in the smart meter data aggregation process is a non-trivial task. Even though the secure data aggregation for the smart meter has been a lot of attention from both academic and industry researchers in recent years, most of these studies are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter system. Recently, blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. In particular, blockchains are identified as having the potential to bring significant benefits and innovation for the electricity consumption network. This study suggests a distributed, privacy-preserving, and simple secure smart meter data aggregation system, backed up by Blockchain technology. Smart meter data are aggregated and verified by a hierarchical Merkle tree, in which the consensus protocol is supported by the practical Byzantine fault tolerance algorithm.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.61-71
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• 2004

XML can describe a wide range of data, from regular to irregular and from flat to deeply nested. Thus, XML is rapidly emerging as the do facto standard for the Web document format since XML supports an efficient data exchange and integration. Also, to retrieve the data represented by XML, several XML query languages are proposed. XML query languages such as XPath and XQuery use path expressions to traverse irregularly structured data which comprise B% elements. To evaluate path expressions, various path indexes are proposed. However, traditional path indexes are constructed by utilizing only the XML data structure. Therefore, in this paper, we propose an adaptive path index which utilizes the XML data structure as well as query workloads. To improve the query performance, the adaptive path index proposed by this paper manages the frequently used paths and the structural summary of the XML data using a hash tree and a graph structure. Experimental results show that the adaptive path index improves the query performance typically 2 to 69 times compared with the existing indexes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.73-83
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• 2018

There has been increasing interest from NIST and other companies in studying post-quantum cryptography in order to resist against quantum computers. Multivariate polynomial based, code based, lattice based, hash based digital signature, and isogeny based cryptosystems are one of the main categories in post quantum cryptography. Among these categories, isogeny based cryptosystem is known to have shortest key length. In this paper, we implemented Supersingular Isogeny Diffie-Hellman (SIDH) protocol efficiently on low-end mobile device. Considering the device's specification, we select supersingular curve on 523 bit prime field, and generate efficient isogeny computation tree. Our implementation of SIDH module is targeted for 32bit environment.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.5 no.1
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• pp.37-50
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• 1995

The smart card with the cryptography and VLSI technologies makes it possible to implement the electronic cash easily. A number of electronic each schemes have been proposed by many cryptographic researchers. In this paper, we propose a practical electronic cash system, using blind digital signature scheme. Schnorr's authentication scheme based on the discrete logarithm problem, and the hierarchical cash tree based on two one-way hash functions for dividable payment. Thisf electronic cash scheme has such properties as privacy of the payment, off-line payment, non-reuseability of cash, transferability of cash to another customer, and dividable payment of cash. This electronic cash protocol is well suited for implementing in smart card.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.153-158
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• 2007

사용자들의 특성에 맞게 개인화되고 세분화된 위치 기반 서비스를 제공하기 위해서는 방대한 이동 객체의 위치 이력 데이터 집합으로부터 유용한 패턴을 추출하여 의미 있는 지식을 탐사하기 위한 시공간 패턴 탐사가 필요하다. 현재까지 다양한 패턴 탐사 기법들이 제안되었으나 이동 패턴들 중 단순히 시공간 제약이 없는 빈발 패턴만을 추출하기 때문에 한정된 시간 범위와 제한적인 영역 범위 내에서의 빈발 패턴을 탐사하는 문제에는 적용하기 어렵다. 또한 패턴 탐사 수행 시 데이터베이스를 반복 스캔하여 탐사 수행시간이 많이 소요되는 문제를 포함하거나 메모리상에 탐사 대상인 후보 패턴 트리를 생성하는 방법을 통해 탐사 시간을 줄일 수는 있으나 이동 객체 수나 최소지지도 등에 따라 트리를 구성하고 유지하는데 드는 비용이 커질 수 있다. 따라서 이러한 문제를 해결하기 위한 효율적인 패턴 탐사 기법의 개발이 요구됨으로써 선행 작업으로 본 논문에서는 상세 수준의 객체 이력 데이터들의 시간 및 공간 속성을 의미 있는 시간영역과 공간영역 정보로 변환하는 시공간 데이터 일반화 방법을 제안한다. 제안된 방법은 공간 개념 계층에 대한 영역 정보들을 영역 Grid 해쉬 테이블(AGHT:Area Grid Hash Table)로 생성하여 공간 인덱스트리인 R*-Tree의 검색 방법을 이용해 이동 객체의 위치 속성을 2차원 공간영역으로 일반화하고, 시간 개념 계층을 생성하여 이동 객체의 시간적인 속성을 시간 영역으로 일반화함으로써 일반화된 데이터 집합을 형성하여 효율적인 이동 객체의 시간 패턴 마이닝을 유도할 수 있다.의 성능을 기대할 수 있을 것이다.onium sulfate첨가배지(添加培地)에서 가장 저조(低調)하였다. vitamin중(中)에서는 niacin과 thiamine첨가배지(添加培地)에서 근소(僅少)한 증가(增加)를 나타내었다.소시켜 항이뇨 및 Na 배설 감소를 초래하는 작용과, 둘째는 신경 경로를 통하지 않고, 아마도 humoral factor를 통하여 신세뇨관에서 Na 재흡수를 억제하는 작용이 복합적으로 나타내는 것을 알 수 있었다.으로 초래되는 복합적인 기전으로 추정되었다., 소형과와 기형과는 S-3에서 많이 나왔다. 이상 연구결과에서 입도분포가 1.2-5mm인 것이 바람직한 것으로 나타났다.omopolysaccharides로 확인되었다. EPS 생성량이 가장 좋은 Leu. kimchii GJ2의 평균 분자량은 360,606 Da이었으며, 나머지 두 균주에 대해서는 생성 EPS 형태와 점도의 차이로 미루어 보아 생성 EPS의 분자구조와 분자량이 서로 다른 것으로 판단하였다.TEX>개로 통계학적으로 유의한 차이가 없었다. Heat shock protein-70 (HSP70)과 neuronal nitric oxide synthase (nNOS)에 대한 면역조직화학검사에서 실험군 Cs2군의 신경세포가 대조군 12군에 비해 HSP70과 nNOS의 과발현을 보였으며, 이는 통계학적으로 유의한 차이를 보였다(p<0.05). nNOS와 HSP70의 발현은 강한 연관성을 보였고(상관계수 0.91, p=0.000), nNOS를 발현하는 세포가 동시에 HSP70도 발현함을 확인할 수 있었다. 결론: 우리는

• Journal of KIISE
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• v.42 no.9
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• pp.1175-1184
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• 2015

Recently, there has been an explosive increase in the volume of multimedia data that is available as a result of the development of multimedia technologies. More and more data is becoming available on a variety of web sites, and it has become increasingly cost prohibitive to have a single data server store and process multimedia files locally. Therefore, many service providers have been likely to outsource data to cloud storage to reduce costs. Such behavior raises one serious concern: how can data users be authenticated in a secure and efficient way? The most widely used password-based authentication methods suffer from numerous disadvantages in terms of security. Multi-factor authentication protocols based on a variety of communication channels, such as SMS, biometric, or hardware tokens, may improve security but inevitably reduce usability. To this end, we present a data block-based authentication scheme that is secure and guarantees usability in such a manner where users do nothing more than enter a password. In addition, the proposed scheme can be effectively used to revoke user rights. To the best of our knowledge, our scheme is the first data block-based authentication scheme for outsourced data that is proven to be secure without degradation in usability. An experiment was conducted using the Amazon EC2 cloud service, and the results show that the proposed scheme guarantees a nearly constant time for user authentication.