• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• Information Systems Review
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• v.18 no.4
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• pp.17-42
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• 2016

Information security incidents caused by authorized insiders are increasing in financial firms, and this increase is particularly increased by outsourced contractors. With the increase in outsourcing in financial firms, outsourced contractors having authorized right has become a threat and could violate an organization's information security policy. This study aims to analyze the differences between own employees and outsourced contractors and to determine the factors affecting the violation of information security policy to mitigate information security incidents. This study examines the factors driving employees to violate information security policy in financial firms based on the theory of planned behavior, general deterrence theory, and information security awareness, and the moderating effects of employee type between own employees and outsourced contractors. We used 363 samples that were collected through both online and offline surveys and conducted partial least square-structural equation modeling and multiple group analysis to determine the differences between own employees (246 samples, 68%) and outsourced contractors (117 samples, 32%). We found that the perceived sanction and information security awareness support the information security policy violation attitude and subjective norm, and the perceived sanction does not support the information security policy behavior control. The moderating effects of employee type in the research model were also supported. According to the t-test result between own employees and outsourced contractors, outsourced contractors' behavior control supported information security violation intention but not subject norms. The academic implications of this study is expected to be the basis for future research on outsourced contractors' violation of information security policy and a guide to develop information security awareness programs for outsourced contractors to control these incidents. Financial firms need to develop an information security awareness program for outsourced contractors to increase the knowledge and understanding of information security policy. Moreover, this program is effective for outsourced contractors.