Abstract
Big data ecosystems are increasingly important for the daily activities of any type of company. They are decisive elements in the organization, so any malfunction of this environment can have a great impact on the normal functioning of the company; security is therefore a crucial aspect of this type of ecosystem. When approaching security in big data as an issue, it must be considered not only during the creation and implementation of the big data ecosystem, but also throughout its entire lifecycle, including operation, and especially when managing and responding to incidents that occur. To this end, this paper proposes an incident response process supported by a private blockchain network that allows the recording of the different events and incidents that occur in the big data ecosystem. The use of blockchain enables the security of the stored data to be improved, increasing its immutability and traceability. In addition, the stored records can help manage incidents and anticipate them, thereby minimizing the costs of investigating their causes; that facilitates forensic readiness. This proposal integrates with previous research work, seeking to improve the security of big data by creating a process of secure analysis, design, and implementation, supported by a security reference architecture that serves as a guide in defining the different elements of this type of ecosystem. Moreover, this paper presents a case study in which the proposal is being implemented by using big data and blockchain technologies, such as Apache Spark or Hyperledger Fabric.
Highlights
To tackle the security challenges stated above, we propose to use blockchain as a distributed ledger to maintain the data needed to address security issues, including all operations performed on data stored in big data, together with the different alerts and warnings produced by the big data ecosystem
We tried to look for proposals as regards the monitoring of the operation of Big Data ecosystems, or studies related to managing the response to incidents in this type of environment; we found only one paper in this sense, on a specific tool that focuses on performance and not on security [18], and another study carried out ten years ago on how to monitor distributed environments [19]
A big data ecosystem is usually a very complex environment, to try to manage its operation it is advisable to have a process based on the main best practices in the industry and that is sufficiently abstract to be applicable to any scenario
Summary
This case study is based on the design and implementation of a hydroponic crop that has different automated sensors and actuators, thanks to a big data ecosystem (cyber-physical system) This big data environment is connected to a private blockchain network, implemented by Hyperledger Fabric, which aims to store all the events produced by the actuators for later analysis through machine learning techniques, such as PCA The main contributions of our paper are : (I) the creation of an abstract incident response process for big data ecosystems, (II) its integration with a general process of creation and implementation of secure big data, (III) a technological proposal to support forensic readiness through the use of blockchain and machine learning technologies, and (IV) a case study, which shows the application of our proposal in a cyber-physical environment.
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