深圳大学学报（理工版）2012，Vol.29Issue(3)：224-229,6.DOI:10.3724/SP.J.1249.2012.03224
基于递进多目标蛙跳优化的LSB±K隐写算法
A secure LSB plus-minus K steganography based on escalating multi-objective SFLA
摘要
Abstract
An escalating multi-objective shuffled frog leaping algorithm (EMO-SFLA) was proposed. In the EMO-SFLA strategies such as non-dominated sorting, crowding distance and population reconstruction were adopted to obtain a diversity and uniformity of the Pareto frontier. Then, an improved least-significant bit plus-minus K steganography (denoted as SFLA-LSBK) was put forward based on EMO-SFLA. In SFLA-LSBK, a matrix denoting all the image blocks was defined as a feasible solution, and the value was shown of each element of the matrix, denoting the embedding bits of the corresponding image block. The difference of the histogram characteristic function center of mass ( HCF-COM) of the cover difference images and its stego version, together with the embedding capacity, were employed as the two objects for optimizing the embedded bits of each image block. Experimental results show that, under similar security levels, SFLA-LSBK has a 30% increase in embedding capacity over LSB Matching steganography, and the LSB Matching steganography was improved with single objective optimization. The proposed method also demonstrates better performance in resisting steganalysis than LSB ± 2 steganography, and the LSB ± 2 steganography is improved with single objective optimization under the same embedding capacity.关键词
数据安全与计算机安全/隐写/混合蛙跳算法/多目标优化Key words
data security and computer security/ steganography/ shuffled frog leaping algorithm/ multi-objective optimization分类
信息技术与安全科学引用本文复制引用
欧阳春娟,李霞,李斌..基于递进多目标蛙跳优化的LSB±K隐写算法[J].深圳大学学报（理工版）,2012,29(3):224-229,6.基金项目
国家自然科学基金资助项目(61171124,61103174) （61171124,61103174）
