关键词：
big data;steganography;carrier-free text steganography;multi-keywords;POS tagging
摘要：
Steganography has attracted more and more attentions in protecting information security. Previous studies achieved by modifying the carriers can't effectively resist the steganalysis methods and attacks. To address this problem, by combining big data with steganography, a novel multi-keywords carrier-free text steganography method based on part of speech tagging is proposed in this paper. In our method, the hidden tags are selected from all the Chinese character components of words. And the POS (Part of Speech) is used to hiding the number of keywords to enhance the hiding capacity. Meanwhile, the redundancy of hidden tags in extraction process is eliminated by ensuring the uniqueness of hidden tags in every stego-text. Also, the way of joint retrieval is used for hiding multi-keywords. The experimental results show that with appropriate hidden tags and large scale of big text data, the proposed method has good performance in the hiding capacity, the success rate of hiding, the extraction accuracy and the time efficiency.
摘要：
Based on the test paper questions the paper summarizes the constraint conditions,and the analysis of mathematical models to explore the genetic algorithm based on the traditional strategy of an intelligent test,the traditional genetic algorithm for an intelligent test strategies to improve,modify the genetic algorithm coding, fitness function,mutation operator and other conditions change,Test Paper based on genetic algorithm to improve policy efficiency test paper,verify the test paper based on genetic algorithm strategy for improving advanced nature of the problem.
