Pairing-based cryptosystems have developed very fast in the last few years. The efficiencies of these cryptosystems depend on the computation of the bilinear pairings, In this paper, a new efficient algorithm based on double-base chains for computing the Tate pairing is proposed for odd characteristic p 〉 3. The inherent sparseness of double-base number system reduces the computational cost for computing the Tate pairing evidently. The new algorithm is 9% faster than the previous fastest method for the embedding degree k = 6.
For steganalysis of JPEG images, features derived in the embedding domain appear to achieve a preferable performance. However, with the existing JPEG steganography, the minor changes due to the hidden secret data are not easy to be explored directly from the quantized block DCT （BDCT） coefficients in that the energy of the carrier image is much larger than that of the hidden signal. In this paper, we present an improved calibration-based universal JPEG steganalysis, where the microscopic and macroscopic calibrations are combined to calibrate the local and global distribution of the quantized BDCT coefficients of the test image. All features in our method are generated from the difference signal be- tween the quantized BDCT coefficients of the test image and its corresponding microscopic calibrated image, or calculated as the difference between the signal extracted from test image and its corresponding macroscopic calibrated image. The extracted features will be more effective for our classification. Moreover, through using the Markov empirical transition matrices, both magnitude and sign dependencies along row scanning and column scanning patterns existed in intra-block and inter-block quantized BDCT coefficients are employed in our method. Experimental results demonstrate that our proposed scheme outperforms the best effective JPEG steganalyzers having been presented.
HUANG FangJun1,2 & HUANG JiWu1,2 1 School of Information Science and Technology,Sun Yat-Sen University,Guangzhou 510275,China
