An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection

In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method,this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection.For the spatial image,this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain.Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography,and use the minimum distortion coding to realize the embedding of the secret messages.Finally,according to the embedding modification amplitude of secret messages in the new embedded domain,the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain.The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation,the bilinear interpolation and the bicubic interpolation.And the average correct extraction rate of embedded messages increases from 50%to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method,compared with the classical steganography algorithm S-UNIWARD.Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation.

Lossless Data Hiding Scheme Based on VQ Index Coding

Lossless data hiding can restore the original status of cover media after embedded secret data are extracted. In 2010, Wang et al. proposed a lossless data hiding scheme which hides secret data in vector quantization （VQ） indices, but the encoding strategies adopted by their scheme expand the final codestream. This paper designs four embedding and encoding strategies to improve Wang et aL＇s scheme. The experiment result of the proposed scheme compared with that of the Wang et aL＇s scheme reduces the bit rates of the final codestream by 4.6% and raises the payload by 1.09% on average.

一种稳健的BIM数据盲水印算法

为了对BIM模型在遭受攻击后进行快速有效的版权保护,提出一种稳健的BIM数据盲水印算法。首先,以原数据中的多面网格要素为单位,提取多面网格对象的所有网格顶点构造复数序列,对复数序列做DFT变换得到幅度系数和相位系数;其次,利用QIM方法,将经过Logistic映射置乱得到的水印信息,嵌入到DFT变换域的幅度系数中;最后,运用离散傅里叶逆变换(inverse discrete fourier transform,IDFT)得到含水印信息的BIM数据。在水印提取中,通过投票原则提取水印,无需原始数据参与,是一种盲水印算法。在实际应用中,因BIM模型中顶点坐标的相同值较多,被用来嵌入水印的有效载体较少,为解决这一问题,在误差容许范围内对原始坐标数据加入了随机噪声,以嵌入不同的水印,间接地增加了水印嵌入容量。实验表明,该算法能够很好的控制水印嵌入引起的数据误差,嵌入水印对BIM数据的精度影响小,且对BIM数据常见的随机删除实体、旋转、平移攻击和特殊攻击具有较好的稳健性,可为BIM数据的所有权提供切实可行的依据。

Evaluation Index System of Urban Identity

In recent years, with the rapid development of urban construction, the maintenance and creation of urban identity has met unprecedented opportunities as well as problems. In light of lacking related evaluation systems of urban identity planning, this paper makes an in-depth study on the composition system of urban identity, based on which it develops an urban identity evaluation system and then proposes technical methods for index screening and evaluation. Finally, it verifi es the application of an urban identity evaluation index system by using quantitative simulation in the two Chinese cities of Tianjin and Nanjing.

Quantization Based Watermarking Methods Against Valumetric Distortions

Most of the quantization based watermarking algorithms are very sensitive to valumetric distortions, while these distortions are regarded as common processing in audio/video analysis. In recent years, watermarking methods which can resist this kind of distortions have attracted a lot of interests. But still many proposed methods can only deal with one certain kind of valumetric distortion such as amplitude scaling attack, and fail in other kinds of valumetric distortions like constant change attack, gamma correction or contrast stretching. In this paper, we propose a simple but effective method to tackle all the three kinds of valumetric distortions. This algorithm constructs an invariant domain first by spread transform which satisfies certain constraints. Then an amplitude scale invariant watermarking scheme is applied on the constructed domain. The validity of the approach has been confirmed by applying the watermarking scheme to Gaussian host data and real images. Experimental results confirm its intrinsic invariance against amplitude scaling, constant change attack and robustness improvement against nonlinear valumetric distortions.

Data Hiding in the Division Domain:Simultaneously Achieving Robustness to Scaling and Additive Attacks

Data hiding plays an important role in privacy protection and authentication,but most data hiding methods fail to achieve satisfactory performance in resisting scaling attacks and additive attacks.To this end,this paper proposes a new quantization index modulation(QIM)variant based on division domains(D-QIM).It can not only resist the above two attacks well,but also adjust the performance trade-offs by controlling the parameters.Simulation results confirm the performance gain of D-QIM in terms of the bit error rate(BER).