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Large-scale steganalysis using outlier detection method for image sharing application

机译:使用离群值检测方法的大规模隐写分析在图像共享中的应用

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In past several years so many steganalysis techniques are emerged but none of them are not efficient for real world image sharing applications where millions of images are transmitted. In small scale steganalysis individual images are detected for suspicious payload. Here uses a different approach to determine most prolific steganographer who sends large volume of secret data in the network. A new technique is introduced to determine the steganographer out of large number of users, where each user transmits numerous images. In this method steganalytic features are extracted from image, distance between users are calculated and finding out the outlier user who deviate from the majority of other users.
机译:在过去的几年中,出现了许多隐写分析技术,但是它们对于传输数百万张图像的真实世界的图像共享应用程序都不是有效的。在小规模的隐写分析中,将检测单个图像中的可疑有效载荷。这里使用另一种方法来确定谁是网络中发送大量秘密数据的最多产的隐写术者。引入了一种新技术来确定大量用户中的隐写术者,其中每个用户都传输大量图像。在这种方法中,从图像中提取隐写特征,计算用户之间的距离,并找出偏离大多数其他用户的异常用户。

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