Sophisticated cyber attacks have plagued many high-profile businesses. To remain aware of the fast-evolving threat landscape, open-source Cyber Threat Intelligence (OSCTI) has received growing attention from the community. Commonly, knowledge about threats is presented in a vast number of OSCTI reports. Despite the pressing need for high-quality OSCTI, existing OSCTI gathering and management platforms, however, have primarily focused on isolated, low-level Indicators of Compromise. On the other hand, higher-level concepts (e.g., adversary tactics, techniques, and procedures) and their relationships have been overlooked, which contain essential knowledge about threat behaviors that is critical to uncovering the complete threat scenario. To bridge the gap, we propose SecurityKG, a system for automated OSCTI gathering and management. SecurityKG collects OSCTI reports from various sources, uses a combination of AI and NLP techniques to extract high-fidelity knowledge about threat behaviors, and constructs a security knowledge graph. SecurityKG also provides a UI that supports various types of interactivity to facilitate knowledge graph exploration.

中文翻译：

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自动化开源威胁情报收集和管理系统

复杂的网络攻击困扰了许多知名企业。为了始终了解快速发展的威胁形势，开源社区网络威胁情报（OSCTI）受到了社区越来越多的关注。通常，有关威胁的知识在大量的OSCTI报告中都有介绍。尽管迫切需要高质量的OSCTI，但是，现有的OSCTI收集和管理平台主要集中在孤立的，低级的危害指标上。另一方面，高层概念（例如，对手战术，技术和程序）及其关系已被忽略，其中包含有关威胁行为的基本知识，这对于揭示完整的威胁情景至关重要。为了弥合差距，我们建议使用SecurityKG，这是一个用于OSCTI自动化收集和管理的系统。SecurityKG从各种来源收集OSCTI报告，结合使用AI和NLP技术提取有关威胁行为的高保真知识，并构建安全知识图。SecurityKG还提供了一个UI，该UI支持各种类型的交互性，以促进知识图的探索。