Early Warning Identity Threat and Mitigation System

Aditya Tyagi, Razieh Nokhbeh Zaeem, K. S. Barber
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引用次数: 1

Abstract

While many organizations share threat intelligence, there is still a lack of actionable data for organizations to proactively and effectively respond to emerging identity threats to mitigate a wide range of crimes. There currently exists no solution for organizations to access current trends and intelligence to understand emerging threats and how to appropriately respond to them.  This research project delivers I-WARN to help bridge that gap. Using a wide range of open-source information, I-WARN gathers, analyzes, and reports on threats related to the theft, fraud, and abuse of Personally Identifiable Information (PII). I-WARN then maps those threats to the MITRE ATT&CK -- a framework that helps understand lateral movement of an attack --  to offer mitigation and risk reduction tactics. I-WARN aims to deliver actionable intelligence, offering early warning into threat behaviors, and mitigation responses.  This paper discusses the technical details of I-WARN, non-exhaustive  current solutions for threat intelligence sharing, and future work.
预警识别、威胁和缓解系统
虽然许多组织共享威胁情报,但仍然缺乏可操作的数据,使组织能够主动有效地应对新出现的身份威胁,以减轻各种犯罪。目前还没有解决方案可以让组织访问当前趋势和情报,以了解新出现的威胁以及如何适当地应对它们。本研究项目提供I-WARN,以帮助弥合这一差距。I-WARN使用广泛的开源信息,收集、分析和报告与盗窃、欺诈和滥用个人身份信息(PII)相关的威胁。然后,I-WARN将这些威胁映射到MITRE ATT&CK(一个有助于了解攻击横向移动的框架),以提供缓解和降低风险的策略。I-WARN旨在提供可操作的情报,为威胁行为和缓解响应提供早期预警。本文讨论了I-WARN的技术细节,非详尽的当前威胁情报共享解决方案,以及未来的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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