Identification of cyber threats is one of the essential tasks for security teams. Currently, cyber threats can be identified using knowledge organized into various formats, enumerations, and knowledge bases. This paper studies the current challenges of identifying vulnerabilities and threats in cyberspace using enumerations and data about assets. Although enumerations are used in practice, we point out several issues that still decrease the quality of vulnerability and threat identification. Since vulnerability identification methods are based on network monitoring and agents, the issues are related to the asset discovery, the precision of vulnerability discovery, and the amount of data. On the other hand, threat identification utilizes graph-based, nature-language, machine-learning, and ontological approaches. The current trend is to propose methods that utilize tactics, techniques, and procedures instead of low-level indicators of compromise to make cyber threat identification more mature. Cooperation between standards from threat, vulnerability, and asset management is also an unresolved issue confirmed by analyzing relationships between public enumerations and knowledge bases. Last, we studied the usability of techniques from the MITRE ATT&CK knowledge base for threat modeling using network monitoring to capture data. Although network traffic is not the most used data source, it allows the modeling of almost all tactics from the MITRE ATT&CK.
翻译:查明网络威胁是安全小组的基本任务之一。目前,利用以各种格式、查点和知识基础组成的知识,可以查明网络威胁。本文件研究目前使用查点和资产数据查明网络空间脆弱性和威胁的挑战。虽然查点和数据在实践中使用,但我们指出若干问题,这些问题仍然降低了脆弱性和威胁识别的质量。由于脆弱性识别方法以网络监测和代理为基础,这些问题与资产发现、脆弱性发现精确度和数据数量有关。另一方面,威胁识别利用图表、自然语言、机器学习和本体学方法。目前的趋势是提出方法,利用战术、技术和程序,而不是低层次的妥协指标,使网络威胁识别更加成熟。威胁、脆弱性和资产管理标准之间的合作也是一个未决问题,通过分析公共查点和知识库之间的关系加以确认。最后,我们研究了麻省、莱特和克公司利用网络监测进行威胁模拟以获取数据的技术的可用性。尽管网络通信不是最常用的数据源,但它允许模拟所有威胁建模。