• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.31-36
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• 2010

In this paper, We propose a transaction signing-based authentication scheme for protecting sinkhole attacks in wireless sensor networks. Sinkhole attack makes packets that flow network pass through attacker. So, Sinkhole attack can be extended to various kind of attacks such as denial of service attacks, selective delivery or data tamper etc. We analyze sinkhole attack methods in directed diffusion based wireless sensor networks. For the purpose of response to attack method, Transaction signing-based authentication scheme is proposed. This scheme can work for those sensor networks which use directed diffusion based wireless sensor networks. The validity of proposed scheme is provided by BAN logic.

• Journal of Korean Society of Archives and Records Management
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• v.13 no.3
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• pp.231-254
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• 2013

The purpose of this study is to survey the problems of the record appraisal system based on value of "Business Transaction (Danwi-gwaje)" and suggest a way to solve the problems in Korean government agencies. This study begins with analyzing the many negative cases of creating wrong "Business Transaction" profiles and making discordances between value of records and value of transaction, through data mainly from focused group interviews of six record professionals in central government agencies. It concludes with suggesting a new records appraisal model that assigns the retention periods to multiple entities to solve the problems of the current record appraisal system.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.629-640
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• 2003

A shared disk (SD) cluster couples multiple nodes for high performance transaction processing, and all the coupled nodes share a common database at the disk level. In the SD cluster, a transaction routing corresponds to select a node for an incoming transaction to be executed. An affinity-based routing can increase local buffer hit ratio of each node by clustering transactions referencing similar data to be executed on the same node. However, the affinity-based routing is very much non-adaptive to the changes in the system load, and thus a specific node will be overloaded if transactions in some class are congested. In this paper, we propose a dynamic transaction routing scheme that can achieve an optimal balance between affinity-based routing and dynamic load balancing of all the nodes in the SD cluster. The proposed scheme is novel in the sense that it can improve the system performance by increasing the local buffer hit ratio and reducing the buffer invalidation overhead.

• Journal of Korea Spatial Information System Society
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• v.5 no.2 s.10
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• pp.69-82
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• 2003

Mobile transactions updating spatial objects are long transactions that update local objects of mobile clients during disconnection. Since a recovered transaction cannot read the write sets of other transactions committed before the recovery due to disconnection, the recovered transaction may conflicts with them. However, aborting of the recovered long transaction leads to the cancellation of all updates including the recovered updates. It is definitely unsuitable to cancel the recovered updates due to the conflicts. In this paper, we propose the recovery scheme to retrieve foreign conflictive objects from the write sets of other transactions for reducing aborting of a recovered transaction. The foreign conflictive objects are part of the data committed by other transactions and may conflict with the objects updated by the recovered transaction. In the scheme, since the recovered transaction can read both the foreign conflictive objects and the recently checkpoint read set, it is possible to reupdate properly the potentially conflicted objects.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.65-85
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• 2009

The main purpose of this paper is to propose a sophistication framework for a global manufacturing network (GMN) driven by a mother company to autonomously propagate and coordinate transaction data that are exchanged among manufacturing partners. The framework is based on conceptual fundamentals of previous research that provide a step toward ultimate successful collaboration in the supply chain and employs mobile agents for the coordination and propagation of transaction data. Maintaining the integrity of transaction data linked to a huge information web is difficult. With the sophistication functionalities of this framework, it becomes easy to effectively control the overall GMN operations and to accomplish the intended goals. The current level of sophistication focuses on the transaction data propagation. The sophistication level may be expanded up to business intelligence in the future.

• The Journal of Economics, Marketing and Management
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• v.9 no.2
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• pp.1-10
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• 2021

Purpose: In this work, we examine several time series models to predict internet and mobile transaction amount in South Korea, whereas Jeong (2020) has obtained the optimal forecasts for online shopping transaction amount by using time series models. Additionally, optimal forecasts based on the model considered can be calculated and applied to the Corona 19 situation. Research design, data, and methodology: The data are extracted from the online shopping trend survey of the National Statistical Office, and homogeneous and comparable in size based on 46 realizations sampled from January 2007 to October 2020. To achieve the goal of this work, both multiplicative ARIMA model and Holt-Winters Multiplicative seasonality method are taken into account. In addition, goodness-of-fit measures are used as crucial tools of the appropriate construction of forecasting model. Results: All of the optimal forecasts for the next 12 months for two online shopping transactions maintain a pattern in which the slope increases linearly and steadily with a fixed seasonal change that has been subjected to seasonal fluctuations. Conclusions: It can be confirmed that the mobile shopping transactions is much larger than the internet shopping transactions for the increase in trend and seasonality in the future.

• Journal of Information Technology Applications and Management
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• v.15 no.4
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• pp.37-59
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• 2008

This study focuses on the antecedents to the privacy concerns and their influence on trust and online transaction intention. Based on previous exploratory works and the literature review of privacy concerns, four antecedents are identified-Internet literacy, social awareness, perceived vulnerability, and perceived ability to information control. Incorporating these antecedents, privacy concerns, trust and online transaction intention, a conceptual model is developed and seven research hypotheses are proposed for empirical testing. The proposed model is examined through structural equation analysis. The results show that Internet literacy, social awareness, and perceived vulnerability have statistically significant effect on the privacy concerns of users and the privacy concerns has a positive influence on the trust. Finally, the trust has a positive effect on the online transaction intention. Implications of these findings are discussed for both researchers and practitioners and future research issues are raised as well.

• The Korean Journal of Franchise Management
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• v.12 no.1
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• pp.35-44
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• 2021

Purpose: This study examines the opportunism moderating effect by the startup experience in the relationship between franchisor and franchisees. In the case of a franchise system that has a continuous relational exchange transaction, relationship management is a very important activity because the relationship management between franchisor and franchisees improves the quality of the relationship. Nevertheless, there is insufficient of research on opportunism, which is a negative factor in managing the relationship between franchisor and franchisees in continuous relationship. Research design, data and methodology: This study, we explore the cause of opportunism based on transaction cost theory through prior research and establish a research model based by goal incongruity, uncertainty, information asymmetry, transaction specific assets, the relevance to determinant of opportunism and the startup experienced which is a moderating variable. To verify several hypotheses, the data were collected from 300 out of 1,760 domestic franchisees and analyzed using multiple regression analysis with SPSS program. Results: The findings are as follows. Goal incongruity did not affect opportunism. Opportunism increased as uncertainty increased, and as information asymmetry increased, opportunism increased. An opportunism decreased as transaction specific assets increased. Moreover, the findings show that startup experience only plays a moderating role in the relationship between information asymmetry and opportunism. Therefore, 4 out of 8 hypotheses were supported. Conclusions: The findings show that uncertainty, information asymmetry, and transaction specific assets are the determinants of opportunism. In addition, the results of the analysis of the moderating role of startup experience show that the less entrepreneurial experience, the greater the influence of information asymmetry on opportunism. Our findings mean that maintaining a successful relationship between franchisors and franchisees is possible when franchisors provide knowledge sharing, goal sharing, environmental sharing, and management information sharing to franchisees. In addition, the findings of this study shows that the contract content and management should be changed according to the entrepreneurial experience. In other words, the franchisors must share and integrate the accumulated franchisees' and franchisors' experience with the franchisees to create a synergy that can lead to successful bilateral relationship maintenance, which in turn reduces opportunism.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2310-2326
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• 2000

Client-server DBMS based on a data-shipping model can exploit e1ient resources effectively by allowing inter-transaction caching. However, inter-transaction caching raises the need of transactional cache consistency maintenancetTCCM protocol. since each client is able to cache a portion of the database dynamically. Deferred locking(DL) is a new detection-based TCCM scheme designed on the basis of a primary copy locking algorithm. In DL, a number of lock ,ujuests and a data shipping request are combined into a single message packet to minimize the communication overhead required for consistency checking. Lsing a simulation model. the performance of the prolxlsed scheme is compared with those of two representative detection based schemes, the adaptive optimistic concurrency control and the caching two-phase locking. The performance results indicate that DL improves the overall system throughput with a reasonable transaction abort ratio over other detection - based schemes.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.