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Articles by Zhihua Xia
Total Records ( 6 ) for Zhihua Xia
  Zhihua Xia , Xingming Sun , Jiaohua Qin and Changming Niu
  Learning-based methodology has been demonstrated to be an effective approach to dispose the steganalysis difficulties due to the variety of image texture. A crucial process of the learning-based steganalysis is to construct a low-dimensional feature set. In this study, a feature selection method based on Hybrid Genetic Algorithm (HGA) is presented to select feature subsets which not only contain fewer features, but also provide better detection performance for steganalysis. First, the general framework about utilizing Genetic Algorithm (GA) to do feature selection for steganalysis is presented. Then, we analyze similarity among individuals (SI) in each generation and the Transformation of Generations (TG) to determine whether the GA has converged into a local area. Next, according to the SI and TG, the restarting operation is incorporated into the HGA to allow the algorithm to escape from the unsatisfactory local area. In the experiments, three feature subsets are formed from a universal feature set for three typical steganography methods, respectively. The experimental results show that the classifiers using the feature subsets gain better detection accuracy and higher speed than those using the universal set.
  Jiaohua Qin , Xingming Sun , Xuyu Xiang and Zhihua Xia
  In this study, a new steganalytic method, which exploits the difference statistics of neighboring pixels, is proposed to detect the presence of spatial LSB matching steganography. In the proposed method, the differences between the neighboring pixels (DNPs), the differences between the local extrema (DLENs) and their neighbors in grayscale histogram are used as distinguishing features and the SVM is adopted to construct classifier. Experimental results show that the proposed method is efficient to detect the LSB matching steganography for the compressed and uncompressed images and outperforms other recently proposed algorithms.
  Zhijie Liu , Xingming Sun , Yuling Liu , Lincong Yang , Zhangjie Fu , Zhihua Xia and Wei Liang
  In some critical application areas, it is not allowed to modify the contents of the text, like military, legal and literature fields. Therefore, restoring the original contents of the text becomes a practical and important issue for text watermarking. This study aims to deal with this problem. We firstly present the concept of reversible text watermarking and then bring forth an effective scheme to achieve reversible text watermarking. Based on the synonym substitution method, the proposed algorithm applies an invertible transform to embed watermark, extract watermark and recover the original contents of the text. By using the reversible watermarking scheme, one can not only protect the interests of the author of the text, but also get the original contents of the text, if the receiver has the wish and right to revert the original contents of the text. Moreover, the scheme improves the payload capacity via using high embedding level, compressing the watermark or repeating the algorithm more than one time.
  Xingming Sun , Shufang Wang , Zhihua Xia and Xinhui Wang
  The advances in digital media make the copyright protection more and more important. Digital watermarking provides a copyright protection solution to this problem. The text is the most popular medium over the internet and many researchers have proposed text watermarking methods in past years. In this study, we propose a new watermarking method based on skeleton algorithm for hiding messages in Chinese text image. In the embedding process, on the basis of character segmentation, the skeleton of each character is extracted and then the location of the bounding box of each skeleton is recorded. Secondly, in each text line, the average center line of the bounding boxes is calculated and the centers of character skeletons are shifted to a position higher or lower than the average center line. The shifting pattern constitutes the watermark. In the extracting process, we firstly conduct the binarization and deskewing operation to the printed-scanned image. Then the remaining phase is very similar to the embedding process. The experimental results prove that the proposed method can successfully resist the print and scan attack and holds much better robustness than that does not use skeleton algorithm.
  Yi Zhu , Xingming Sun , Zhihua Xia , Li Chen , Tao Li and Daxing Zhang
  With the growing popularity of cloud computing, more and more users are willing to outsource their private data to the cloud. To ensure the security of data, data owners usually encrypted their private data before outsourcing them to the cloud server. Though data encryption improves the security of data, it increases the difficulty of data operating. This study focuses on the search of encrypted images in the cloud and proposes an efficient similarity retrieval scheme over encrypted images. The proposed scheme enables data owners to outsource their personal images and the content-based image retrieval service to the cloud without revealing the actual content of the image database to the cloud. The proposed scheme in this study supports the global feature based image retrieval methods under the Euclidean distance metric. Besides, rigorous security analysis and extensive experiments show that the proposed scheme is secure and efficient.
  Zhiqiang Ruan , Xingming Sun , Wei Liang , Decai Sun and Zhihua Xia
  In this study, we focus on design efficient security techniques to maximize chances of data survival in wireless sensor networks, which involve disconnected or unattended operation with periodic visited by the sink, we refer to such networks as UWSNs. Data security in such UWSNs poses a number of challenges when applied in security-sensitive environments. First, sensors must accumulate data for a long time until it can be off loaded to a periodic sink. The adversary has lots of time to mount various attacks that aim to learn, erase, or modify potentially valuable data collected and held by sensors. Second, there is no ever-present sink, thus real time detection dose not help and the adversary can reach its goal and remain undetected. To address these security problems, we present CADS, a novel Co-operative and Anti-fraud Data Storage scheme for UWSNs by integrating the techniques of secret sharing and Discrete Logarithm Problem (DLP). We first propose a share generation and distributed scheme to achieve reliable and fault-tolerant initial data storage by providing redundancy for original data components, we then utilize discrete logarithm problem to ensure the integrity of the distributed data shares. The proposed scheme enables individual sensors to verify all the related data shares simultaneously in the absence of the original data in each round. Security analysis and simulations show that the proposed scheme has resistance against node capture attacks and outperforms existing security scheme in terms of data survival quantity and false negative probability.
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