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UPSI Digital Repository (UDRep)
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| Abstract : |
| This paper presents a new approach based on multi-dimensional evaluation and benchmarking for data hiding techniques, i.e., watermarking and steganography. The novelty claim is the use of evaluation matrix (EM) for performance evaluation of data hiding techniques; however, one major problem with performance evaluation of data hiding techniques is to ¯nd reasonable thresholds for performance metrics and the trade-o® among them in di®erent data hiding applications. Two experiments are conducted. The ¯rst experiment included LSB techniques (eight approaches) based on di®erent payload results and the noise gate approach; a total of nine approaches were used. Five audio samples with di®erent audio styles are tested using each of the nine approaches and considering three evaluation criteria, namely, complexity, payload, and quality, to generate watermarked samples. The second experiment involves the use of various decision-making techniques simple additive weighting (SAW), multiplicative exponential weighting (MEW), hierarchical adaptive weighting (HAW), technique for order of preference by similarity to ideal solution (TOPSIS), weighted sum model (WSM) and weighted product method (WPM) to benchmark the results of the ¯rst experiment. Mean, standard deviation (STD), and paired sample t-test are then performed to compare the correlations among di®erent techniques on the basis of ranking results. The ¯ndings are as follows: (1) A statistically signi¯cant di®erence is observed among the ranking results of each multi-criteria decision-making (MCDM) technique, (2) TOPSIS-Euclidean is the best technique to solve the benchmarking problem among digital watermarking techniques. (3) Among the decisionmaking techniques, WSM has the lowest rank in terms of solving the benchmarking problem. (4) Under di®erent circumstances, the noise gate watermarking approach performs better than LSB algorithms |
| References |
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