开发和扩展可视化分析解决方案，用于对诈骗活动进行调查分析
Lessons Learned Developing and Extending a Visual Analytics Solution for Investigative Analysis of Scamming Activities
摘要：
网络安全分析师在大型通信数据集上工作，通过仔细检查数千封电子邮件对话来进行调查分析，以找到潜在的诈骗活动和网络骗子网络。传统上，专家使用电子邮件客户端，数据库系统和文本编辑器来执行此调查。随着技术的发展，通过使用最先进的数据可视化技术来更有效地汇总数据的精心制作的工具已经出现。Beagle[1]就是这样一个工具，它使用不同的面板可视化大型通信数据，以便检查员有更好的机会找到诈骗网络。本文是关于我们实施和改进Jay Koven等人[1]所做工作的报告。我们已经提出并通过实现演示了一些可视化，我们认为这些可视化将有助于更有效地对电子邮件数据进行分组和分析。最后，我们还介绍了一个案例研究，展示了我们的工具在现实世界中的潜在用途。
英文摘要：
Cybersecurity analysts work on large communication data sets to perform investigative analysis by painstakingly going over thousands of email conversations to find potential scamming activities and the network of cyber scammers. Traditionally,experts used email clients, database systems and text editors to perform this investigation. With the advent of technology,elaborate tools that summarize data more efficiently by using cutting edge data visualization techniques have come out. Beagle[1] is one such tool which visualizes the large communication data using different panels such that the inspector has better chances of finding the scam network. This paper is a report on our work to implement and improve the work done by Jay Koven et al. [1]. We have proposed and demonstrated via implementation, a few more visualizations that we feel would help in grouping and analyzing the e-mail data more efficiently. Lastly, we have also presented a case study that shows the potential use of our tool in a real-world scenario.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
