A data representation for system behavior telemetry for scalable big data security analytics is presented, affording telemetry consumers comprehensive visibility into workloads at reduced storage and processing overheads. The new abstraction, SysFlow, is a compact open data format that lifts the representation of system activities into a flow-centric, object-relational mapping that records how applications interact with their environment, relating processes to file accesses, network activities, and runtime information. The telemetry format supports single-event and volumetric flow representations of process control flows, file interactions, and network communications. Evaluation on enterprise-grade benchmarks shows that SysFlow facilitates deeper introspection into attack kill chains while yielding traces orders of magnitude smaller than current state-of-the-art system telemetry approaches -- drastically reducing storage requirements and enabling feature-filled system analytics, process-level provenance tracking, and long-term data archival for cyber threat discovery and forensic analysis on historical data.
翻译:提供可缩放的大数据安全分析的系统行为遥测数据,为遥测消费者提供在减少储存和处理间接费用的工作量方面全面可见度。新的抽象系统SysFlow是一个紧凑的开放数据格式,它将系统活动的代表性提升为以流动为中心的对象关系图谱,记录应用程序如何与环境互动,与文件存取、网络活动和运行时间信息有关的程序。遥测格式支持流程控制流程、文件互动和网络通信的单一事件和量体流。企业级基准评估显示,SysFlow有助于更深入地对攻击杀手链进行回溯性研究,同时产生比目前最先进的系统远程测量方法规模较小的跟踪序列 -- -- 大幅减少存储要求,并使得具有特性的系统能够进行分析、流程级的源码跟踪,以及用于对历史数据进行网络威胁发现和法证分析的长期数据存档。