Abstract: The paper presented a reversible image authentication scheme for VQ images using codebook clustering. The proposed method not only locates the alterations of VQ images but also recover the indexes of VQ image without any distortion from the marked VQ indexes after the hidden authentication bits have been extracted. The method uses the codebook clustering to generate four fixed-size small codebooks. Those small codebookswere used to encode original image to obtain a watermarked VQ image. The proposed method has two advantages. Firstly, the hidden procedure of the proposed method is the same as VQ encoding. After the image is finished encoded, the watermarked image is generated. Secondly, the proposed method does not cause any distortion of indexes of VQ image after we extract the hidden data from the watermarked VQ image.

• Publication Date: 04-Aug-2013
• DOI: 10.15224/978-981-07-7227-7-10
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Abstract: Ubiquitous data mining (UDM) is a methodology for creating new knowledge by building an integrated financial database in a ubiquitous computing environment, extracting useful rules by using diverse rule-extraction-based data mining techniques, and combining these rules. In this study, we built six credit rating forecasting models using traditional statistical methods (i.e., logistic regression and Bayesian networks), multilayer perceptron (i.e., MLP), classification tree algorithms (i.e., C5.0), neural network rule extraction algorithms (i.e., NeuroRule), and UDM in order to predict personal credit ratings. To verifythe feasibility and effectiveness of UDM, credit ratings and credit loan data provided by A Financial Group in Korea were used in this study. Empirical results indicated that UDM outperforms other single traditional classifiers such as logistic regression, neural networks, frequency matrix, C5.0, and NeuroRule. UDM always outperforms other single classifiers in credit ratin

• Publication Date: 04-Aug-2013
• DOI: 10.15224/978-981-07-7227-7-09Ubiquitous data mining (UDM), Ubiquitous computing environment, Credit rating forecasting models, Rule extraction algorithms, Integrated financial database
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