A User-Centric and Sentiment Aware Privacy-Disclosure Detection Framework based on Multi-input Neural Network
A User-Centric and Sentiment Aware Privacy-Disclosure Detection Framework based on Multi-input Neural Network
复制标题
DOI：
--
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Nuhil Mehdy;Hoda Mehrpouyan
中科院分区：
文献类型：
--
作者：
Nuhil Mehdy;Hoda Mehrpouyan
数据和信息隐私是当今世界的一个主要问题。更具体地说，随着信息共享技术的进步，用户的数字隐私已经成为需要处理的最重要的问题之一。越来越多的用户通过短信、电子邮件和社交媒体分享信息，而没有适当意识到隐私威胁及其后果。防止私人信息泄露的一种方法是在对话中识别他们，并在发送者和接收者之间发生传输之前警告调度员。防止信息（敏感）丢失的另一种方法可能是在数据已经在某处积累时分析和清理一批离线文档。然而，自动化识别文本数据中以用户为中心的隐私泄露的过程是具有挑战性的。这是因为自然语言具有极其丰富的形式和结构，具有不同程度的歧义。因此，我们询问了一个潜在的框架，可以通过考虑内容的作者身份和情感（语气）以及语言特征和技术来精确识别用户在一段文本中的隐私披露，从而将这一挑战带到可及的范围内。建议的框架被认为是支持插件，以帮助文本分类系统更准确地识别可能会泄露作者的个人或私人信息的文本。
Data and information privacy is a major concern of today’s world. More specifically, users’ digital privacy has become one of the most important issues to deal with, as advancements are being made in information sharing technology. An increasing number of users are sharing information through text messages, emails, and social media without proper awareness of privacy threats and their consequences. One approach to prevent the disclosure of private information is to identify them in a conversation and warn the dispatcher before the conveyance happens between the sender and the receiver. Another way of preventing information (sensitive) loss might be to analyze and sanitize a batch of offline documents when the data is already accumulated somewhere. However, automating the process of identifying user-centric privacy disclosure in textual data is challenging. This is because the natural language has an extremely rich form and structure with different levels of ambiguities. Therefore, we inquire after a potential framework that could bring this challenge within reach by precisely recognizing users’ privacy disclosures in a piece of text by taking into account - the author-ship and sentiment (tone) of the content alongside the linguistic features and techniques. The proposed framework is considered as the supporting plugin to help text classification systems more accurately identify text that might disclose the author’s personal or private information.