Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/2/724 |
| _version_ | 1818490962541805568 |
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| author | Julio Moreno Manuel A. Serrano Eduardo B. Fernandez Eduardo Fernández-Medina |
| author_facet | Julio Moreno Manuel A. Serrano Eduardo B. Fernandez Eduardo Fernández-Medina |
| author_sort | Julio Moreno |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T17:23:56Z |
| format | Article |
| id | doaj.art-dac5f187da4a49f984ef4afaa512ab2f |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-10T17:23:56Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-dac5f187da4a49f984ef4afaa512ab2f2022-12-22T01:39:54ZengMDPI AGApplied Sciences2076-34172020-01-0110272410.3390/app10020724app10020724Improving Incident Response in Big Data Ecosystems by Using Blockchain TechnologiesJulio Moreno0Manuel A. Serrano1Eduardo B. Fernandez2Eduardo Fernández-Medina3GSyA Research Group, University of Castilla-La Mancha, 13071 Ciudad Real, SpainAlarcos Research Group, University of Castilla-La Mancha, 13071 Ciudad Real, SpainComputer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USAGSyA Research Group, University of Castilla-La Mancha, 13071 Ciudad Real, SpainBig 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.https://www.mdpi.com/2076-3417/10/2/724big data securityblockchainincident responseforensic readiness |
| spellingShingle | Julio Moreno Manuel A. Serrano Eduardo B. Fernandez Eduardo Fernández-Medina Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies Applied Sciences big data security blockchain incident response forensic readiness |
| title | Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies |
| title_full | Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies |
| title_fullStr | Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies |
| title_full_unstemmed | Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies |
| title_short | Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies |
| title_sort | improving incident response in big data ecosystems by using blockchain technologies |
| topic | big data security blockchain incident response forensic readiness |
| url | https://www.mdpi.com/2076-3417/10/2/724 |
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