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Among various digital image formats used in our daily life, the joint photographic experts group (JPEG) is the most popular. Therefore, reversible data hiding (RDH) in JPEG images is important and useful for many applications such as archive management and image authentication. However, RDH in JPEG images is considerably more difficult than that in uncompressed images because the information redundancy in JPEG images is less than that in uncompressed images and any modification in the compressed domain may introduce more distortion in the host image. Furthermore, along with the embedding capacity and fidelity (visual quality) that have to be considered for uncompressed images, the storage size of the marked JPEG file should be considered. In this paper, based on the philosophy behind the JPEG encoder and the statistical properties of discrete cosine transform (DCT) coefficients, we present some basic insights on how to select quantized DCT coefficients for RDH. Then, a new histogram shifting-based RDH scheme for JPEG images is proposed, in which the zero coefficients remain unchanged and only coefficients with values 1 and -1 are expanded to carry message bits. Moreover, a block selection strategy based on the number of zero coefficients in each 8×8 block is proposed, which can be utilized to adaptively choose DCT coefficients for data hiding. Experimental results demonstrate that by using the proposed method, we can easily realize high embedding capacity and good visual quality. The storage size of the host JPEG file can also be well preserved.

Lately, EEG-based authentication has received considerable attention from the scientific community. However, the limited usability of wet EEG electrodes as well as low accuracy for large numbers of users have so far prevented this new technology to become commonplace. In this study a novel EEGbased authentication system is presented, which is based on the RSVP paradigm and uses a knowledge-based approach for authentication. 29 subjects' data were recorded and analyzed with wet EEG electrodes as well as dry ones. A true acceptance rate of 100% can be reached for all subjects with an average required login time of 13.5 s for wet and 27.0 s for dry electrodes. Average false acceptance rates for the dry electrode setup were estimated to be 3.33·10 -5 .

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