论文标题
关于隐藏自然语言系统的信息
On Information Hiding in Natural Language Systems
论文作者
论文摘要
在当今数字世界中，随着数据隐私而不是奢侈品的必要性，对更强大的隐私保护和信息安全模型的研究正在上升。在本文中，我们查看了自然语言隐藏在自然语言系统中的信息，以实现数据安全性和机密性。我们总结了有关这些系统的保密和不可知地要求的主要挑战，并提出了改进的潜在方向，特别是针对隐志文本质量。我们认为，这项研究将充当合适的框架，以建立更有弹性的自然语言隐肌模型，以在基于自然语言的神经模型中灌输安全性。
With data privacy becoming more of a necessity than a luxury in today's digital world, research on more robust models of privacy preservation and information security is on the rise. In this paper, we take a look at Natural Language Steganography (NLS) methods, which perform information hiding in natural language systems, as a means to achieve data security as well as confidentiality. We summarize primary challenges regarding the secrecy and imperceptibility requirements of these systems and propose potential directions of improvement, specifically targeting steganographic text quality. We believe that this study will act as an appropriate framework to build more resilient models of Natural Language Steganography, working towards instilling security within natural language-based neural models.
