A Measuring Method for Hadoop Platform Based on Trusted Computing

Abstract

The invention discloses a Hadoop platform measuring method based on dependable computing. The method comprises the steps that S1, measurement is performed before a Map Reduce program runs, wherein a MapReduce program file in a Hadoop platform is obtained and comprises job.jar, job.split and job.xml; an abstract value of the Map Reduce program file is calculated, a PCR is expanded, and meanwhile the value is written into a Map Reduce program measurement log; S2, dynamic measurement is performed on the Hadoop file, wherein Hadoop core assembly information is obtained and includes a Hadoop configuration file, a Hadoop local library, a Hadoop core jar packet and a Hadoop core script; an abstract value of each file of the Hadoop core assembly is calculated, the PCR is expanded, and meanwhile the values are written into a Node Manager node measurement log; the abstract value of each file of the Hadoop core assembly are compared with a standard value in a standard library, and a Node Manager node health detection result is obtained. By adopting the technical scheme, a credible link is adopted as the basic extension credible relation, measurement of an application layer for the Map Reduce program is achieved, and meanwhile, on the basis of the Hadoop node health detection mechanism, the dynamic Hadoop platform integrity measurement is provided.

Description

technical field [0001] The invention relates to the technical fields of cloud computing and trusted computing, in particular to a measuring method for a Hadoop platform based on trusted computing. Background technique [0002] With the rapid development of information technology, the scale of enterprise data shows an explosive growth trend. Due to its high reliability, scalability, on-demand service and many other advantages, cloud computing is used by many enterprises to store and process enterprise data. Hadoop is one of the cloud computing solutions. As an open source project of the Apache Foundation, Hadoop has inherited the functions of Google GFS and Google MapReduce and is available for free. It has received a lot of research and application in academia and industry. Build your own Hadoop platform. [0003] However, at the beginning of the design of Hadoop, security issues were not considered, resulting in a large number of security issues in the current use process...

AI Technical Summary

Problems solved by technology

[0006] However, the existing technology measures the system environment starting from the hardware, and only measures the application layer

As a distributed computing model of Hadoop, MapReduce provides a distributed processing method for big data, but its integrity is not verified during the actual measurement process, which leads to the possibility that the MapReduce program running on the Hadoop platform may be tampered with, resulting in unsafe Belief in Computational Behavior

At the same time, IMA only measures the relevant files during the startup process of Hadoop. During the whole process of Hadoop running, the dynamic credibility of the platform is difficult to be effectively protected.

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