Human Aspects of Information Security, Privacy and Trust - 5th International Conference, HAS 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings
Human Aspects of Information Security, Privacy and Trust - 5th International Conference, HAS 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings
复制标题
信息安全、隐私和信任的人为方面 - 第五届国际会议，HAS 2017，作为 HCI International 2017 的一部分举行，加拿大不列颠哥伦比亚省温哥华，2017 年 7 月 9-14 日，会议记录
DOI：
10.1007/978-3-319-58460-7_19
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Al Moubayed N
中科院分区：
文献类型：
--
作者：
Al Moubayed N
成功的网络安全依赖于处理来自各种来源的大量数据，如警方报告、博客、情报报告、安全公告和新闻来源。这导致大量非结构化文本数据难以手动管理或调查。在本文中，我们介绍了一个工具，总结，分类和模型，这样的数据集沿着与搜索引擎查询的数据产生的模型。搜索引擎可以用来寻找链接，不同的文件之间的相似之处和差异，在某种程度上超越了目前的搜索方法。该工具基于概率主题建模技术，该技术比文档的词法分析更进一步，以模拟单词，文档和抽象主题之间的微妙关系。它将帮助研究人员查询隐藏在文档中的底层模型，并进入文档库，允许它们按主题排序。
Successful Cybersecurity depends on the processing of vast quantities of data from a diverse range of sources such as police reports, blogs, intelligence reports, security bulletins, and news sources. This results in large volumes of unstructured text data that is difficult to manage or investigate manually. In this paper we introduce a tool that summarises, categorises and models such data sets along with a search engine to query the model produced from the data. The search engine can be used to find links, similarities and differences between different documents in a way beyond the current search approaches. The tool is based on the probabilistic topic modelling technique which goes further than the lexical analysis of documents to model the subtle relationships between words, documents, and abstract topics. It will assists researchers to query the underlying models latent in the documents and tap into the repository of documents allowing them o be ordered thematically.