ABSTRACT

To effectively protect sensitive information, this paper proposes a method of text Emotional modulation steganography based on machine learning. Firstly, we explore an intelligent dynamic expansion method for text emotional lexicon based on deep learning in detail. Secondly, the cosine similarity algorithm is used to combine the two most similar emotional words into emotional word pairs, which is the basis of the proposed approach. Thirdly, we combine emotional word pairs with matrix encoding algorithm to calculate the minimum modification unit, so as to minimize the rewriting of carrier text, and hence improve the privacy, embedding rate and capacity of sensitive information. Fourthly, we evaluate and validate the proposed algorithms through several experiments. Finally, the design of a NoC based organizational covert and secure autonomous intelligent online team work system is carried out. Experiments show that the efficiency, security, concealment and robustness of the proposed algorithms are sound.

摘要

为了有效保护敏感信息，本文提出了一种基于机器学习的文本情感调制隐写方法。首先，我们详细探索了一种基于深度学习的文本情感词库智能动态扩展方法。其次，利用余弦相似度算法将两个最相似的情感词组合成情感词对，这是该方法的基础。第三，将情感词对与矩阵编码算法相结合，计算最小修改单元，从而最大限度地减少载体文本的重写，从而提高敏感信息的隐私性、嵌入率和容量。第四，我们通过几个实验评估和验证了所提出的算法。最后，设计了一个基于NoC的组织隐蔽安全自治智能在线团队工作系统。实验表明，所提算法的效率、安全性、隐蔽性和鲁棒性是合理的。