• Journal of Digital Convergence
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• v.11 no.11
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• pp.343-349
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• 2013

Rough set theory comes to derive optimal rules through the effective selection of features from the redundancy of lots of information in data mining using the concept of equivalence relation and approximation space in rough set. The reduction of attributes is one of the most important parts in its applications of rough set. This paper purports to define a information-theoretic measure for determining the most important attribute within the association of attributes using rough entropy. The proposed method generates the effective reduct set and formulates the core of the attribute set through the elimination of the redundant attributes. Subsequently, the control rules are generated with a subset of feature which retain the accuracy of the original features through the reduction.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.265-273
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• 2000

In relational database management systems(RDBMS), a table consIn relational database management systems(RDBMS), a table consists of sets of records which are composed of a set of attributes. The number of distinct values(NDV) of an attribute denotes the number of distinct attribute values that actually appear in the database records, and is widely used in optimizing queries and supporting statistic queries. Object-relational database management systems(ORBBMSS), however, support the inheritance between tables which enforces an attribute defined in a super-table to be inherited in sub-tables automatically. Hence, in ORDBMSS, not only NDV of an attribute In a single table but also NDV of an attribute in multiple tables(HNDV) is needed. In this paper, we propose a method that calculates HNDV using arrays of attribute value intervals. In this method, an array of attribute value intervals is created for an attribute of interest In each table in a table hierarchy, and HNDV can be calculated or estimated by merging the arrays of attribute value intervals. The proposed method accurately calculates HNDV using small additional storage space and is efficient for an environment where only some of the tables in a table hierarchy are frequently updated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2646-2659
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• 2017

Equipped with the advantages of flexible access control and fine-grained authentication, attribute based signcryption is diffusely designed for security preservation in many scenarios. However, realizing efficient key evolution and reducing the calculation costs are two challenges which should be given full consideration in attribute based cryptosystem. In this paper, we present a key-policy attribute based signcryption scheme (KP-ABSC) with delegated computation and efficient key updating. In our scheme, an access structure is embedded into user's private key, while ciphertexts corresponds a target attribute set. Only the two are matched can a user decrypt and verify the ciphertexts. When the access privileges have to be altered or key exposure happens, the system will evolve into the next time slice to preserve the forward security. What's more, data receivers can delegate most of the de-signcryption task to data server, which can reduce the calculation on client's side. By performance analysis, our scheme is shown to be secure and more efficient, which makes it a promising method for data protection in data outsourcing systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.122-127
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• 1998

This paper suggests an integrated method for discovering knowledge from a large database. Our approach applies an attribute-oriented concept hierarchy ascension technique to extract generalized data from actural data in databases, induction of decision trees to measure the value of information, and knowledge reduction of rough set theory to remove dispensable attributes and attribute values. The integrated algorithm first reduce the size of database for the concept generalization, reduces the number of attributes by way of elimination condition attributes which have little influence on decision attribute, and finally induces simplified decision rules removing the dispensable attribute values by analyzing the dependency relationships among the attributes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1597-1605
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• 2015

Password authenticated key exchange (PAKE) is a protocol that a client stores its password to a server, authenticates itself using its password and shares a session key with the server. In multi-server PAKE, a client splits its password and stores them to several servers separately. Unless all the servers are compromised, client's password will not be disclosed in the multi-server setting. In attribute-based encryption (ABE), a sender encrypts a message M using a set of attributes and then a receiver decrypts it using the same set of attributes. In this paper, we introduce multi-server PAKE protocol that utilizes a set of attributes of ABE as a client's password. In the protocol, the client and servers do not need to create additional public/private key pairs because the password is used as a set of public keys. Also, the client and the servers exchange only one round-trip message per server. The protocol is secure against dictionary attacks. We prove our system is secure in a proposed threat model. Finally we show feasibility through evaluating the execution time of the protocol.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.550-556
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• 2000

This paper comes to derive optimal decision rule from incomplete information using the concept of indiscernibility relation and approximation space in Rough set. As there may be some errors in case that processing information contains multiple or missing data, the method of removing or minimizing these data is required. Entropy which is used to measure uncertainty or quantity in information processing field is utilized to remove the incomplete information of rough relation database. But this paper does not always deal with the information system which may be contained incomplete information. This paper is proposed object relation entropy and attribute relation entropy using Rough set as information theoretical measures in order to remove the incomplete information which may contain condition attribute and decision attribute of information system.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.161-176
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• 2005

In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.27-33
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• 2017

To efficiently provide cloud computing services to users over the Internet, IT resources must be configured in the data center based on virtualization and distributed computing technology. This paper focuses specifically on the problem that new training data can be added at any time in a wide range of fields, and new attributes can be added to training data at any time. In such a case, rule generated by the training data with the former attribute set can not be used. Moreover, the rule can not be combined with the new data set(with the newly added attributes). This paper proposes further development of the new inference engine that can handle the above case naturally. Rule generated from former data set can be combined with the new data set to form the refined rule.

• Language and Information
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• v.16 no.1
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• pp.25-43
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• 2012

This study introduces set-denoting time expressions in Korean, which can be divided into simple and complex types. It was found that while the simple type expressions are easily represented within ISO-TimeML, a time-expression markup language, some complex type set-denoting expressions are not. Therefore, this study analyzes the reason for these difficulties in representing complex type expressions, as well as suggests the introduction of @measure and @interpretation attributes in the TIMEX3 tag. The @measure attribute represents the time interval, and the @interpretation attribute is used to distinguish distributive readings from cumulative readings. Additionally this paper suggests that a mapping between these and other attributes are required in TLINK.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.