基于Hadoop的大数据信息安全监控云平台设计与研究

针对传统的大数据信息监控云平台模式单一、虚拟化程度不高,容易导致信息泄露的问题,为了提高对大数据的信息安全溯源能力,提出基于Hadoop的大数据信息安全监控云平台设计方法。在信息资源云体系下构建大数据信息安全融合模型,通过信息挖掘与匹配方法把云平台中的数据资源、物理资源进行关联性整合,方便数据安全溯源,在Hadoop平台下构建多源信息资源云,建立用户接口注册机制,采用虚拟化技术进行信息保护,实现在云平台下进行信息安全溯源。实验结果表明,采用该方法进行大数据信息安全溯源,大数据信息分类存储性能较好,对异常数据挖掘精度较高。具有较好的信息安全保护能力,确保了信息安全。

Design and research of large data information security monitoring cloud platform based on Hadoop

In view of the traditional big data information monitoring cloud platform mode single, virtualization degree is not high, easily lead to the problem of information disclosure, in order to improve information security traceability of large data capacity, big data information security monitoring based on Hadoop cloud platform design method. Under the system of information resource cloud build big data fusion model of information security through the method of information mining and match the data in a cloud platform correlation integration of resources, physical resources, security, convenience data in Hadoop cloud platform to build multi-source information resources, set up the mechanism of registered user interface, using virtualization technology to information protection and realization of information security in the stage YunPing traceability. The experimental results show that by using this method for large data information security, big data information classification storage performance is good, the abnormal high precision data mining. Has better ability in information security protection, ensure the information security..