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首页> 外文期刊>IEEE transactions on multimedia >Steganographic Security Analysis From Side Channel Steganalysis and Its Complementary Attacks
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Steganographic Security Analysis From Side Channel Steganalysis and Its Complementary Attacks

机译：侧通道隐星分析的隐写安全分析及其互补攻击

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Side channel steganalysis refers to detecting a steganographer in social websites via behavior analysis. In this paper, we first design a side channel steganalysis based on the correlation between image sequences of social users, which aims to find out the behaviorally anomalous steganographer. According to the experimental results of side channel steganalysis, it is intuitively secure for the steganographer to act identically to normal social users since she can avoid being detected by side channel steganalysis. However, when faced with various detection methods, is it still secure to behave similar to a normal user? To comprehensively consider the detection means and further explore the secure behavior region of the steganographer, we design a complementary attack of side channel steganalysis. Specifically, we take the correlation of contents of images as side information and take the images with similar content as references to calibrate steganalysis features, which helps improve traditional steganalysis. The proposed side channel steganalysis and its complementary attack efficiently detect steganographers from two different aspects. When the average rank of the steganographer is used to measure the performance, side channel steganalysis can rank the steganographer within the top ten in 100 actors, and the complementary attack can raise the average rank of the steganographer by three places compared with the previous method. From the perspective of the steganographer on social networks, it can help her behave in a more secure region, where her behavior should neither deviate from that of normal users nor be too similar to that of normal users.
机译：侧沟杀死通过行为分析是指通过行为分析检测社交网站中的托克光师。在本文中，我们首先根据社会用户的图像序列与社会用户序列之间的相关性设计侧沟道分析，旨在找到行为异常的steganographer。根据侧通道沉淀的实验结果，它直观地为勒克斯人同意，因为她可以避免被侧通道塞巴巴分析检测。但是，当面对各种检测方法时，表现得类似于普通用户仍然是安全的？为了全面地考虑检测手段并进一步探索带臭者的安全行为区域，我们设计了侧通道沉淀的互补攻击。具体地，我们将图像的内容与侧面信息相关联，并将具有与校准麻木分析特征的引用相似的图像，这有助于改善传统的隐星分析。所提出的侧沟道沉淀及其互补攻击有效地检测两个不同方面的隐钉记录人。当STEGANoGrapher的平均等级用于测量性能时，侧通道塞巴巴分析可以将带臭者排名在100个演员的前十个内，并且与先前的方法相比，互补攻击可以将三个地点的平均等级提高三个地方。从Seganographer对社交网络的角度来看，它可以帮助她在更安全的区域中表现，在那里她的行为应该偏离普通用户的行为，也不应该与普通用户的行为偏离。

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