【摘要】：該文提出了一種基于LWE(Learning With Errors)算法的密文域可逆隱寫方案,利用LWE公鑰密碼算法對(duì)數(shù)據(jù)加密,用戶在密文中嵌入隱藏信息,對(duì)于嵌入信息后的密文,用戶使用隱寫密鑰可以有效提取隱藏信息,使用解密密鑰可以無(wú)差錯(cuò)恢復(fù)出加密前數(shù)據(jù)實(shí)現(xiàn)了提取過(guò)程與解密過(guò)程的可分離。通過(guò)推導(dǎo)方案在解密與提取信息過(guò)程中出錯(cuò)的概率,得到直接影響方案正確性的參數(shù)為所選噪聲的標(biāo)準(zhǔn)差,實(shí)驗(yàn)獲得并驗(yàn)證了標(biāo)準(zhǔn)差的合理取值區(qū)間;通過(guò)推導(dǎo)嵌入后密文的分布函數(shù),分析密文統(tǒng)計(jì)特征的變化情況,論證了嵌入密文的隱藏信息的不可感知性。該方案是在密文域進(jìn)行的可逆隱寫,與原始載體無(wú)關(guān),適用于文本、圖片、音頻等各類載體。實(shí)驗(yàn)仿真結(jié)果表明該方案不僅能夠保證可逆隱寫的可靠性與安全性,而且1 bit明文在密文域最大可負(fù)載1 bit隱藏信息。
[Abstract]:In this paper, a reversible steganography scheme in ciphertext domain based on LWE (Learning With Errors) algorithm is proposed. The data is encrypted by LWE public key cryptography algorithm. Users embed hidden information in ciphertext. The steganography key can be used to extract the hidden information effectively, and the decryption key can be used to recover the pre-encryption data without error, which can separate the extraction process from the decryption process. By deducing the probability of error in the process of decrypting and extracting information, the parameters directly affecting the correctness of the scheme are the standard deviation of the selected noise. The reasonable range of the standard deviation is obtained and verified by the experiment. By deducing the distribution function of embedded ciphertext and analyzing the change of statistical features of ciphertext, the inperceptibility of hidden information of embedded ciphertext is proved. The scheme is reversible steganography in the ciphertext field, independent of the original carrier, suitable for text, picture, audio and other kinds of carriers. The experimental results show that the proposed scheme can not only guarantee the reliability and security of reversible steganography, but also can load 1 bit hidden information in the ciphertext domain.
【作者單位】： 武警工程大學(xué)電子技術(shù)系網(wǎng)絡(luò)與信息安全武警部隊(duì)重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金(61379152;61272492)~~
【分類號(hào)】：TN918.4
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本文編號(hào)：2297274