• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5671-5693
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• 2017

With the rapid development of cloud computing, more and more data owners are motivated to outsource their data to cloud for various benefits. Due to serious privacy concerns, sensitive data should be encrypted before being outsourced to the cloud. However, this results that effective data utilization becomes a very challenging task, such as keyword search over ciphertexts. Although many searchable encryption methods have been proposed, they only support exact keyword search. Thus, misspelled keywords in the query will result in wrong or no matching. Very recently, a few methods extends the search capability to fuzzy keyword search. Some of them may result in inaccurate search results. The other methods need very large indexes which inevitably lead to low search efficiency. Additionally, the above fuzzy keyword search methods do not support access control. In our paper, we propose a searchable encryption method which achieves fuzzy search and access control through algorithm design and Ciphertext-Policy Attribute-based Encryption (CP-ABE). In our method, the index is small and the search results are accurate. We present word pattern which can be used to balance the search efficiency and privacy. Finally, we conduct extensive experiments and analyze the security of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.8 no.1
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• pp.156-165
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• 2003

The purpose of this study is concerned with possibilistic decision making model (PDMM) that can be used to help CEO and information systems managers decide which information systems should be selected. The application of IT which has influence on rapidly changed environment of enterprise plays an important role in enterprise's activity. When enterprise outsource IT, it is very important to select vendors that reflect goals and constraints of organization. For this purpose, mathematical model in which possibilistic programming is applied is suggested in this study. Although many researches have conducted in conventional programming and stochastic programming. they are still limited in solving practical problems and imprecise/uncertain situations. Multiple decision making model in which impreciseness of input variable is considered can be constructed in PDMM.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.240-257
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• 2006

In an effort to gain competitiveness, recently many companies are trying to outsource their logistics activities to the logistics specialists, while concentrating on their core and strategic business area. Because of this trend, the third party logistics comes to the fore, catching people's attention, and expanding its market rapidly. Under these circumstances, the third party logistics companies are making every effort to improve their logistics services and to develop an information system in order to enhance their competitiveness. In particular, among these efforts one of the critical parts is the decision support system for effective transportation network planning. To this end, this study has developed an efficient decision support system for an optimal transportation network planning by comprehensively considering the transportation mode, routing, assignment, and schedule. As a result of this study, the new system enables the expansion of the third party logistics companies' services including the multimodal transportation, not to mention one mode of transportation, and also gets them ready to plan an international transportation network.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5171-5189
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• 2016

With the popularity of cloud computing, many data owners outsource their graph data to the cloud for cost savings. The cloud server is not fully trusted and always wants to learn the owners' contents. To protect the information hiding, the graph data have to be encrypted before outsourcing to the cloud. The adjacent vertex search is a very common operation, many other operations can be built based on the adjacent vertex search. A boolean adjacent vertex search is an important basic operation, a query user can get the boolean search results. Due to the graph data being encrypted on the cloud server, a boolean adjacent vertex search is a quite difficult task. In this paper, we propose a solution to perform the boolean adjacent vertex search over encrypted graph data in cloud computing (BASG), which maintains the query tokens and search results privacy. We use the Gram-Schmidt algorithm and achieve the boolean expression search in our paper. We formally analyze the security of our scheme, and the query user can handily get the boolean search results by this scheme. The experiment results with a real graph data set demonstrate the efficiency of our scheme.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.979-986
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• 2021

Online food delivery and food delivery apps have continued to grow exponentially in Malaysia. Fundamental aspects in entrepreneurship of the food and beverage industry, such as knowledge and attitudes towards online food delivery services being outsourced, have yet to be extensively recognized. The present study intends to explore this area of subject matter within the Malaysian context by using behavioral reasoning theory. The actual interview for this study took place in May 2020, and 14 interviews had been carried out. All interviews were audio-recorded with the consent from the respondents for reference purposes and subsequently transcribed verbatim. The transcripts were then checked against audio records. Content analysis was used to analyze the transcripts by focusing on n frequency counts and coding of themes. A qualitative method has been adopted by employing an interview to elicit the perspectives of entrepreneurs from Sarawak on the determinants and barriers in outsourcing online food delivery services. Results indicate that high potential in revenue, broad exposure to reach customers, convenience, and provision of job opportunities are the four factors that determine to outsource. In contrast, food quality maintenance, trustworthiness, high cost incurred, and consumer technology resistance are four factors that serve as barriers towards outsourcing third-party online delivery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4742-4770
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• 2019

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.145-150
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• 2021

The trend of globalization leads an increased need for international freight transportation and accelerates the development of the international logistics industry. The objective of this paper is to identify the critical factors that affect the choice of logistics service provider (LSP). The data sample was collected through a questionnaire, responded by 218 companies that outsource logistics services. The analysis uses descriptive statistics; exploratory factor analysis (EFA) and regression analysis were conducted with SPSS. The role of capabilities, customer service, and company reputation were evaluated and tested. Our findings show that capabilities and customer service have a considerable impact on the choice of LSP. The findings also indicate that company reputation do not have significant impact on the choice of LSP. They also showed that the capabilities is the variable that has the most significant effect on the choice of LSP. An implication of this study is that the competition should not only focus on pricing, but should be extended to improving enterprises capabilities, i.e., upgrading human resources, modernizing the modes of transportation, expanding business geographically and developing new technologies. Our study provides LSP managers with insights into how to meet customer expectations in the competitive logistics service sector.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.235-250
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• 2021

Purpose - This study analyzed the correlation and influence between social support, trust (seller, brand), and continuous purchase intention in C2C social commerce in China. Design/methodology/approach - To test the hypothesis, SPSS and Smart PLS 3.0 statistical packages were used based on the collected data. Findings - First, it was confirmed that social support (emotional support, informational support) had a positive effect on trust in sellers. Second, it was found that trust in sellers had a positive effect on brand trust. Third, both seller trust and brand trust have a positive effect on consumers' continuous purchase intention. Research implications or Originality - When consumers gain emotional and informational support from sellers, trust in sellers will be effectively improved. Companies wishing to improve brand credibility of their products will have to outsource the sale of their products to trusted sellers. The C2C social commerce platform should build its own trust rating system, recommend sellers with high reliability ratings, and encourage sellers to provide consumers with a lot of information about their brand.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.140-150
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• 2024

Database-as-a-Service is one of the prime services provided by Cloud Computing. It provides data storage and management services to individuals, enterprises and organizations on pay and uses basis. In which any enterprise or organization can outsource its databases to the Cloud Service Provider (CSP) and query the data whenever and wherever required through any devices connected to the internet. The advantage of this service is that enterprises or organizations can reduce the cost of establishing and maintaining infrastructure locally. However, there exist some database security, privacychallenges and query performance issues to access data, to overcome these issues, in our recent research, developed a database security model using a deterministic encryption scheme, which improved query execution performance and database security level.As this model is implemented using a deterministic encryption scheme, it may suffer from chosen plain text attack, to overcome this issue. In this paper, we proposed a new model for cloud database security using nondeterministic encryption, order preserving encryption, homomorphic encryptionand database distribution schemes, andour proposed model supports execution of queries with equality check, range condition and aggregate operations on encrypted cloud database without decryption. This model is more secure with optimal query execution performance.