首页> 外文会议>International Joint Conference on e-Business and Telecommunications >Enriching Threat Intelligence Platforms Capabilities
【24h】

Enriching Threat Intelligence Platforms Capabilities

机译:丰富威胁情报平台功能

获取原文

摘要

One of the weakest points in actual security detection and monitoring systems is the data retrieval from Open Source Intelligence (OSINT), as well as how this kind of information should be processed and normalized, considering their unstructured nature. This cybersecurity related information (e.g., Indicator of Compromise -IoC) is obtained from diverse and different sources and collected by Threat Intelligence Platforms (TIPs). In order to improve its quality, such information should be correlated with real-time data coming from the monitored infrastructure, before being further analyzed and shared. In this way, it could be prioritized, allowing a faster incident detection and response. This paper presents an Enriched Threat Intelligence Platform as a way to extend import, quality assessment processes, and information sharing capabilities in current TIPs. The platform receives structured cyber threat information from multiple sources, and performs the correlation among them with both static and dynamic data coming from the monitored infrastructure. This allows the evaluation of a threat score through heuristic-based analysis, used for enriching the information received from OSINT and other sources. The final result, expressed in a well defined format, is sent to external entities, which is further used for monitoring and detecting incidents (e.g., SIEMs), or for more in-depth analysis, and shared with trusted organizations.
机译:实际安全检测和监测系统中最薄弱的点是来自开源智能(Osint)的数据检索,以及考虑到其非结构化性质,应如何处理和标准化这种信息。这种网络安全相关信息(例如,妥协的指标)是从不同的和不同来源获得的,并由威胁情报平台(提示)收集。为了提高其质量,在进一步分析和共享之前,此类信息应与来自受监控基础设施的实时数据相关联。以这种方式,可以优先考虑,允许更快的事件检测和响应。本文提出了一个丰富的威胁情报平台,作为扩展当前提示的导入,质量评估流程和信息共享能力的一种方式。该平台从多个源接收结构化Cyber​​威胁信息,并利用来自受监控基础架构的静态和动态数据来执行它们之间的相关性。这允许通过基于启发式的分析评估威胁评分,用于丰富从索坦和其他来源收到的信息。以良好定义的格式表示的最终结果被发送到外部实体,其进一步用于监视和检测事件(例如,SIEM)或更深入的分析,并与可信组织共享。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号