• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3274-3297
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• 2021

Permission delegation is an important research issue in access control. It allows a user to delegate some of his permissions to others to reduce his workload, or enables others to complete some tasks on his behalf when he is unavailable to do so. As an ideal solution for controlling read access on outsourced data objects on the cloud, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has attracted much attention. Some existing CP-ABE schemes handle the read permission delegation through the delegation of the user's private key to others. Still, these schemes lack the further consideration of granularity and traceability of the permission delegation. To this end, this article proposes a flexible and fine-grained CP-ABE key delegation approach that supports white-box traceability. In this approach, the key delegator first examines the relations between the data objects, read permission thereof that he intends to delegate, and the attributes associated with the access policies of these data objects. Then he chooses a minimal attribute set from his attributes according to the principle of least privilege. He constructs the delegation key with the minimal attribute set. Thus, we can achieve the shortest delegation key and minimize the time of key delegation under the premise of guaranteeing the delegator's access control requirement. The Key Generation Center (KGC) then embeds the delegatee's identity into the key to trace the route of the delegation key. Our approach prevents the delegatee from combining his existing key with the new delegation key to access unauthorized data objects. Theoretical analysis and test results show that our approach helps the KGC transfer some of its burdensome key generation tasks to regular users (delegators) to accommodate more users.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.103-115
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• 2001

This paper proposes the two algorithms which generate a minimal decision rule and approximate inference operation, adapted the rough set and the factor space theory in fuzzy knowledge base. The generation of the minimal decision rule is executed by the data classification technique and reduct applying the correlation analysis and the Bayesian theorem related attribute factors. To retrieve the specific object, this paper proposes the approximate inference method defining the membership function and the combination operation of t-norm in the minimal knowledge base composed of decision rule. We compare the suggested algorithms with the other retrieval theories such as possibility theory, factor space theory, Max-Min, Max-product and Max-average composition operations through the simulation generating the object numbers and the attribute values randomly as the memory size grows. With the result of the comparison, we prove that the suggested algorithm technique is faster than the previous ones to retrieve the object in access time.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.65-73
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• 2011

In rough set literatures, methods for inducing minimal rules from a given decision table have been proposed. When the decision attribute is ordinal, inducing rules about upward and downward unions of decision classes is advantageous in the simplicity of obtained rules. However, because of independent applications of the rule induction method, inclusion relations among upward/downward unions in conclusion parts are not inherited to the condition parts of obtained rules. This non-inheritance may debase the quality of obtained rules. To ensure that inclusion relations among conclusions are inherited to conditions, we propose two rule induction approaches. The performances of the proposed approaches considering the inclusion relations between conclusions are examined by numerical experiments.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.34-43
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• 2002

Since traditional static metadata set like Dublin Core has static metadata attributes about bibliography information, integration of metadata for various metadata, problems about standard and extension of metadata must be considered for applying it to new environment. Specially, as event-driven metadata write method included the notion of e-commerce come out for interoperability in digital libraries, traditional metadata management which cannot distinguish between different kinds of update operations to new extension of metadata set occurs unsuitable waiting of update operation. So, improvement is needed about it. In this paper, we show whether alleviative transaction consistency can be applied to digital library or not. Also it would divide newer metadata into static metadata attribute connected in read operation within user read-only transaction and dynamic metadata attribute in update operation within dynamic(e-commerce) update transactions. We propose newer metadata management algorithm considered in classfication of metadata attributes and dynamic update transaction. Using two version for minimal maintenance cost and ARU(Appended Refresh Unit) for dynamic update transaction, to minimize conflict between read and write operations shows fast response time and high recency ratio. As a result of the performance evaluation, we show our algorithm is proved to be better than other algorithms in newer metadata environments.