Shi-Jinn Horng

TL;DR: A secure scheme that can achieve the security and privacy requirements, and overcome the weaknesses of SPECS is provided, and the efficiency merits of the scheme are shown through performance evaluations in terms of verification delay and transmission overhead.

TL;DR: This paper presents an approach for dynamic maintenance of approximations w.r.t. objects and attributes added simultaneously under the framework of decision-theoretic rough set (DTRS) using equivalence feature vector and matrix and extensive experimental results verify the effectiveness of the proposed methods.

TL;DR: Experimental results on six UCI datasets shown that the proposed dynamic algorithm achieves significantly higher efficiency than the static algorithm and the combination of two reference incremental algorithms.

TL;DR: Improved adaptive performance of the proposed scheme is in resistant to several types of attacks in comparison with the previous schemes; the adaptive performance refers to the adaptive parameter of the luminance masking functioned to improve the performance or robustness of an image from any attacks.

TL;DR: The experimental results show that the watermarked image looks visually identical to the original and the watermark can be effectively extracted upon image processing attacks.