CAREER: Developing Robust Longitudinal Indicators and Early Warnings of Cybercrime

职业：开发稳健的纵向指标和网络犯罪预警

• 批准号: 1652610
• 负责人: Tyler Moore
• 金额: $ 42.1万
• 依托单位: University of Tulsa
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1652610&HistoricalAwards=false
• 关键词: CAREER; Developing; Robust; Longitudinal; Indicators

The proliferation of cybercrime has created an opportunity for researchers to study cybersecurity using a data-driven, and ultimately scientific, approach. This project seeks to improve the process of cybercrime data collection and analysis for the purpose of reducing its harm. Effort-based indicators, which measure the impact of defender actions such as the time taken to clean a compromised resource, are being constructed for use in analyzing data gathered on multiple categories of cybercrime. Indicators are being collected throughout the duration of the project in order to enable longitudinal analysis, for example, to measure any improvements that result from dissemination. It is also being investigated whether it is feasible to devise and deploy a prototype early-warning system that proactively alerts defenders quickly enough to arrest concentrated spikes in cybercriminal activity. The project's educational objective is to advance the science of cybersecurity by contributing public datasets of cybercriminal activity to be shared with other researchers and incorporated into curriculum modules. Instructional initiatives include improving existing curricula and publishing stand-alone resources that can be adopted by others.The project is advancing understanding of how to construct reliable cybercrime indicators. Effort-based indicators help mitigate information asymmetries, so that anyone can see which defenders are working harder to clean up compromised resources. This could in turn improve the response to cybercrime overall by solving coordination problems in which individual defenders shirk responsibility. The project is also advancing understanding of how the response to cybercrime changes over time by collecting data for several years. If widely shared, the indicators can help incentivize defenders to fight cybercrime over the long term. The project seeks to identify not only how to construct the indicators, but also what is the most effective way to share them. The early-warning system, if successful, could greatly enhance the efficiency of countermeasures by helping defenders get ahead of the shifting tactics used by attackers. In the education program supported by the project, datasets are being added to curriculum modules that teach scientific approaches to cybersecurity. Modules are being designed for not only graduate and undergraduate degree programs, but also for middle and high school students, free online courses co-developed by the PI, and a security economics textbook under development.

网络犯罪的扩散为研究人员提供了一个机会，使他们能够使用数据驱动的方法来研究网络安全，最终采用科学的方法。该项目力求改进网络犯罪数据收集和分析过程，以减少其危害。正在构建基于努力的指标，用于衡量防御者行动的影响，例如清理受损资源所花费的时间，以用于分析收集的关于多种类型网络犯罪的数据。在整个项目期间正在收集指标，以便进行纵向分析，例如衡量传播所带来的任何改进。目前还在调查是否可以设计和部署一个预警系统原型，以足够快的速度主动向维护者发出警报，以阻止网络犯罪活动的集中爆发。该项目的教育目标是通过提供网络犯罪活动的公共数据集与其他研究人员共享并纳入课程模块，推进网络安全科学。教学举措包括改进现有课程和出版可供他人采用的独立资源，该项目正在促进对如何构建可靠的网络犯罪指标的理解。基于努力的指标有助于缓解信息不对称，这样任何人都可以看到哪些维护者正在努力清理受损的资源。这反过来又可以通过解决个别维护者推卸责任的协调问题，改善对网络犯罪的总体应对措施。该项目还通过收集数年的数据，推动了解应对网络犯罪的对策如何随着时间的推移而变化。这些指标如果得到广泛分享，将有助于激励维权者长期打击网络犯罪。该项目不仅寻求确定如何构建指标，而且还寻求确定共享指标的最有效方式。预警系统如果成功，可以帮助防御者领先于攻击者使用的变化战术，从而大大提高对策的效率。在该项目支持的教育计划中，数据集被添加到教授网络安全科学方法的课程模块中。模块不仅为研究生和本科学位课程设计，也为初中和高中学生设计，PI共同开发的免费在线课程，以及正在开发的安全经济学教科书。

项目成果

Ten years of attacks on companies using visual impersonation of domain names

使用域名视觉模仿对公司进行的十年攻击

• 发表时间: 2020
• 期刊: Proceedings of the APWG Symposium on Electronic Crime Research
• 作者: Simpson, Geoffrey;Moore, Tyler;Clayton, Richard
• 通讯作者: Clayton, Richard

Empirical analysis of losses from business-email compromise

商业电子邮件泄露造成的损失的实证分析

• 发表时间: 2020
• 期刊: Proceedings of the APWG Symposium on Electronic Crime Research
• 作者: Simpson, Geoffrey;Moore, Tyler
• 通讯作者: Moore, Tyler

The County Fair Cyber Loss Distribution: Drawing Inferences from Insurance Prices

县公平网络损失分布：从保险价格中推断

• DOI: 10.1145/3434403
• 发表时间: 2021
• 期刊: Digital Threats: Research and Practice
• 作者: Woods, Daniel W.;Moore, Tyler;Simpson, Andrew C.
• 通讯作者: Simpson, Andrew C.