基于Spark大数据平台的云上用户日志行为审计系统

User Log Behavior Audit System on Cloud Based on Spark Big Data Platform

网络安全已经逐渐成为一个全球性的问题,受到各行各业的高度重视。除了采用一些主动措施来提高系统的安全性,还可以通过审计来提高网络的安全性。针对这一现状,设计了基于Spark大数据平台的云上用户日志行为审计系统,通过追踪用户的访问内容和访问方式进而查找系统所存的安全隐患,从而规避相应风险的过程和操作集合。主要描述了流程挖掘、数据泄露、数据追溯等系统设计的关键技术和关键模块实现。解决了未标签化的海量用户日志流处理的核心问题,对基于云的系统的日志审计技术发展具有重要意义。

Cyber security gradually becomes a global issue that is highly valued by all walks of life.In addition to adopting some proactive measures to improve the security of the system,auditing can also improve the security of the network.In response to this status quo,a user log behavior audit system on cloud based on Spark big data platform is designed to find the security risks of the system by tracking user’s access content and access mode,and thus avoid the corresponding risky process and operation collection.This paper mainly describes the key technologies and key module implementation of system design such as process mining,data leakage,data tracing,etc.It solves the core problem of untagged massive user log stream processing and is of great significance to the development of log audit technology for cloud-based systems.