Research on Image Steganography Information Detection Based on Support Vector Machine

L. Wenyuan, Wang Jian
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引用次数: 2

Abstract

With the rapid development of the internet of things and cloud computing, users can instantly transmit a large amount of data to various fields, with the development of communication technology providing convenience for people's life, information security is becoming more and more important. Therefore, it is of great significance to study the technology of image hiding information detection. This paper mainly uses the support vector machine learning algorithm to detect the hidden information of the image, based on a standard image library, randomly selecting images for embedding secret information. According to the bit-plane correlation and the gradient energy change of a single bit-plane after encryption of an image LSB matching algorithm, gradient energy change is selected as characteristic change, and the gradient energy change is innovatively applied to a support vector machine classifier algorithm, And has very good detection effect and good stability on the dense image with the embedding rate of more than 40 percent. Keywords-Support Vector Machine; Information Detection; LSB Matching; Steganography
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基于支持向量机的图像隐写信息检测研究
随着物联网和云计算的快速发展,用户可以瞬间将大量数据传输到各个领域,随着通信技术的发展为人们的生活提供便利,信息安全变得越来越重要。因此,研究图像隐藏信息检测技术具有十分重要的意义。本文主要利用支持向量机器学习算法检测图像的隐藏信息,在标准图库的基础上,随机选择图像进行隐藏信息的嵌入。根据图像LSB匹配算法的位面相关性和单个位面加密后的梯度能量变化,选择梯度能量变化作为特征变化,创新地将梯度能量变化应用到支持向量机分类器算法中,对密集图像具有很好的检测效果和很好的稳定性,嵌入率达到40%以上。关键词:支持向量机;信息检测;LSB匹配;隐写术
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